Augmented reality system

Abstract

The disclosure concerns an augmented reality method in which visual information concerning a real-world object, structure or environment is gathered and a deformation operation is performed on that visual information to generate virtual content that may be displayed in place of, or additionally to, real-time captured image content of the real-world object, structure or environment. Some particular embodiments concern the sharing of visual environment data and/or information characterizing the deformation operation between client devices.

Description

BACKGROUND

Augmented reality (AR) refers to using computer generated enhancements to add new information into images in a real-time or near real-time fashion. For example, video images of a wall output on a display of a device may be enhanced with display details that are not present on the wall, but that are generated to appear as if they are on the wall by an augmented reality system. Such systems require a complex mix of image capture information that is integrated and matched with the augmented reality information that is to be added to a captured scene in a way that attempts to seamlessly present a final image from a perspective determined by the image capture device.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Various ones of the appended drawings merely illustrate example embodiments of the present disclosure and should not be considered as limiting its scope.

To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.

FIG. 1A is a block diagram showing an example messaging system for exchanging data (e.g., messages and associated content) over a network.

FIG. 1B is a block diagram showing further details of certain applications and subsystems hosted in an application server, such as the application server in FIG. 1A.

FIG. 2 is a schematic diagram illustrating certain operations of a client device according to example embodiments.

FIG. 3 is a schematic diagram illustrating an exemplary technique for generating a texture map and 3D mesh at a client device according to certain example embodiments.

FIG. 4 is a schematic diagram illustrating an exemplary technique for tracking changes in localization of a client device.

FIG. 5 illustrates the application of a transformation on a 3D mesh in accordance with certain example embodiments.

FIGS. 6A and 6B illustrate the display of captured image views and augmented image views in a device in accordance with certain example embodiments.

FIGS. 7A and 7B illustrate a transformation effect in accordance with certain embodiments of the present invention.

FIGS. 8A and 8B illustrate a transformation effect in accordance with other embodiments of the present invention.

FIG. 9 is a block diagram illustrating a representative software architecture, which may be used in conjunction with various hardware architectures herein described.

FIG. 10 is a block diagram illustrating components of a machine, according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein.

DETAILED DESCRIPTION

Glossary

“CLIENT DEVICE” in this context refers to any machine that interfaces to a communications network to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, desktop computer, laptop, portable digital assistants (PDAs), smartphones, tablets, ultrabooks, netbooks, laptops, multi-processor systems, microprocessor-based or programmable consumer electronics, game consoles, set-top boxes, or any other communication device that a user may use to access a network.

“COMMUNICATIONS NETWORK” in this context refers to one or more portions of a network that may be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, a network or a portion of a network may include a wireless or cellular network and the coupling may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other long range protocols, or other data transfer technology.

“EPHEMERAL MESSAGE” in this context refers to a message that is accessible for a time-limited duration. An ephemeral message may be a text, an image, augmented reality content, a video and the like. The access time for the ephemeral message may be set by the message sender. Alternatively, the access time may be a default setting or a setting specified by the recipient. Regardless of the setting technique, the message is transitory.

“CARRIER SIGNAL” in this context refers to any intangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such instructions. Instructions may be transmitted or received over the network using a transmission medium via a network interface device and using any one of a number of well-known transfer protocols.

“MACHINE-READABLE MEDIUM” in this context refers to a component, device or other non-transitory, tangible media able to store instructions and data temporarily or permanently and may include, but is not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory (EEPROM)) and/or any suitable combination thereof. The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions. The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., code) for execution by a machine, such that the instructions, when executed by one or more processors of the machine, cause the machine to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. Unless qualified by the term “non-transitory”, the term “machine-readable medium” should also be taken to include carrier signals and other transitory media capable of storing instructions and data temporarily or permanently.

“COMPONENT” in this context refers to a device, physical entity or logic having boundaries defined by function or subroutine calls, branch points, application program interfaces (APIs), or other technologies that provide for the partitioning or modularization of particular processing or control functions. Components may be combined via their interfaces with other components to carry out a machine process. A component may be a packaged functional hardware unit designed for use with other components and a part of a program that usually performs a particular function of related functions. Components may constitute either software components (e.g., code embodied on a machine-readable medium) or hardware components. A “hardware component” is a tangible unit capable of performing certain operations and may be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware components of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware component that operates to perform certain operations as described herein. A hardware component may also be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware component may include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component may be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware component may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware components become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware component mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. Accordingly, the phrase “hardware component” (or “hardware-implemented component”) should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware components are temporarily configured (e.g., programmed), each of the hardware components need not be configured or instantiated at any one instance in time. For example, where a hardware component comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware components) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware component at one instance of time and to constitute a different hardware component at a different instance of time. Hardware components can provide information to, and receive information from, other hardware components. Accordingly, the described hardware components may be regarded as being communicatively coupled. Where multiple hardware components exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware components. In embodiments in which multiple hardware components are configured or instantiated at different times, communications between such hardware components may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware components have access. For example, one hardware component may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware component may then, at a later time, access the memory device to retrieve and process the stored output. Hardware components may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information). The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented components that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented component” refers to a hardware component implemented using one or more processors. Similarly, the methods described herein may be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented components. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an Application Program Interface (API)). The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented components may be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented components may be distributed across a number of geographic locations.

“PROCESSOR” in this context refers to any circuit or virtual circuit (a physical circuit emulated by logic executing on an actual processor) that manipulates data values according to control signals (e.g., “commands”, “op codes”, “machine code”, etc.) and which produces corresponding output signals that are applied to operate a machine. A processor may, for example, be a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Radio-Frequency Integrated Circuit (RFIC) or any combination thereof. A processor may further be a multi-core processor having two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously.

“TIMESTAMP” in this context refers to a sequence of characters or encoded information identifying when a certain event occurred, for example giving date and time of day, sometimes accurate to a small fraction of a second.

SUMMARY

The following relates to augmented reality image processing and reproduction of augmented reality content. Some particular embodiments describe obtaining visual information concerning a real-world object, structure or environment and applying a deformation operation on that visual information to generate virtual content that may be displayed in place of, or additionally to, real-time captured image content of the real-world object, structure or environment. Some particular embodiments describe using an initial rough location estimate to identify visual environment data, including 3D point cloud models, texture data and façade data, that describe objects, buildings, structures etc. that are local to that initial rough location estimate. Some particular embodiments describe processing of images captured by a client device to generate visual environment data, including 3D point cloud models, texture data and façade data, that describe real-world objects, buildings, structures etc. Some particular embodiments concern the sharing of visual environment data and/or information characterizing the deformation operation between client devices.

The description that follows includes systems, devices, and methods that illustrate embodiments of the disclosure. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art, that embodiments of the inventive subject matter may be practiced without these specific details. In general, well-known instruction instances, protocols, structures, and techniques are not necessarily shown in detail.

Augmented reality, as described herein, refers to systems and devices that capture images of real-world objects or environments in the field of view of a capture device or user and enhance those images with additional information, and then present the enhanced information on a display. This enables, for example, a user to capture a video stream of a scene or environment using a camera function of a smartphone or wearable device, and an output display of the smartphone or wearable device to present the scene as visible to the user along with additional information. This additional information may include placing virtual objects in the scene or environment so the virtual objects are presented as if they existed in the scene. Aspects of such virtual objects are processed to occlude the virtual object if another real or virtual object passes in front of the virtual object as shown from the perspective of the image sensor capturing the environment. Such virtual objects are also processed to maintain their relationship with real objects as both real and virtual objects move over time, and as the perspective (i.e. orientation, pose and/or location) of the image sensor capturing the environment changes. Examples of virtual objects include video images, still content, text information, three dimensional animations and hologram representations, conventional multimedia content displayed upon a virtual two dimensional surface overlaying a blank real-world wall, and visual effects applied to at least a portion of the output display of a user device.

For clarity, the terms “real” and “real-world” are used herein to refer to objective physical reality. Images of real, material, objects and environments may be captured in a physical image capture device, such as a digital camera, and these images will replicate the user's own perception of such objects or environments. The term “real” contrasts with “virtual”, the latter term denoting the operation of computer simulation. Augmented reality (AR) may therefore be considered to represent an intermediate level of abstraction in a continuum between objective reality and a fully simulated or “virtual” reality (VR). AR, as used herein, therefore refers to a reality that mixes real and virtual elements to varying degrees. Where the virtual elements dominate, some authors would adopt the term “augmented virtuality”. For simplicity, the term augmented reality is used here to refer to any mixed reality, specifically including (real-element dominated) “augmented reality” and “augmented virtuality”.

A number of issues arise when attempting to balance the needs for a close correlation between real and virtual objects, maintenance in real-time, and acceptable processing burden. When “dressing” real-world, three dimensional (3D) structures with virtual objects, the scale of the 3D structure can mean that any detailed model used to represent the structure when generating and applying the virtual objects may require significant levels of computation power, potentially degrading the ability to reproduce and maintain the virtual object in real-time.

The generation of suitable models of 3D structures as an environment in which virtual content is applied can be performed in advance of the reproduction of the virtual content by a user device such as a smartphone or wearable device.

One approach to 3D modelling relies on the processing of large sets of images (ranging from sets of the order of thousands of images to large-scale data sets having tens of millions of images) all related to a particular environment, architectural or natural structure or location. The constituent images may be collated from images captured by a plurality of devices (such as consumer smartphones and digital cameras). Such “crowdsourced” image data sets may vary greatly in terms of appearance and quality and are not likely to be synchronized with other such images.

Other image data sets may be collected by harnessing the image capture facilities of dedicated image capture devices (e.g., digital cameras and unmanned aerial vehicle (UAV)-borne image capture equipment), which in principle provides greater consistency and control over the resulting data set.

In each case, the captured images are stored, typically uploaded to distributed storage devices, for future redistribution and/or processing (e.g. stored on a cloud-based storage facility).

The task facing the modeler is to recover the 3D geometry and appearance of the 3D scene from 2D photographs/videos captured from multiple viewpoints. A first step is often to gather together images according to associated data—a geolocation in metadata or an image title indicating the target of the image, for instance. Associated images may then be processed to extract 3D points that may be used to anchor spatial relationships with other images from other camera poses. Clearly, the use of dedicated image capture devices at known locations, poses, etc. allows the modeler to construct a data asset with easily discovered data associations.

In a technique known as Structure from Motion (SfM), associated images (i.e. plural two-dimensional images of a collection of 3D points, assumed to be static 3D points, from different perspectives) are processed to generate a 3D geometry having the greatest probability of being a match to the data in each of the images. The resulting 3D geometry may be represented as a 3D point cloud (or “sparse 3D model”) or a 3D polygon mesh of vertices.

A point cloud is a set of data points in a coordinate system. The coordinate system may for example be a Cartesian coordinate system (i.e. (x,y,z)-coordinates), a cylindrical coordinate system or a spherical coordinate system.

Examples of SfM techniques include the generation of descriptors for certain features of the images in the data set (BRIEF) and the application of corner detection (ORB).

Filtering processes may be used to remove portions of the point cloud corresponding to moving or dynamic surfaces and to points that provide limited information (e.g. redundant points within a flat surface). In addition to the use of 3D point cloud data, some embodiments may also use additional types of environment data

Each vertex in the 3D mesh (or point in the point cloud representing the 3D geometry) may by mapped (by a mapping) to respective texture data at texture coordinates in a texture map. The mapping is sometimes referred to as a “UV mapping”, so-called because the coordinates in the texture map are conventionally referred to as “u” and “v”.

Registration of the device in an environment for which a suitable model has been prepared may comprise using satellite-based global positioning systems (e.g. GPS) or other location-based systems to identify an initial rough location estimate. Map databases may then be looked up to determine whether a suitable 3D model is already available for a 3D structure or environment at the particular location identified by the identified rough location estimate.

In the absence of a ready-prepared 3D model of a real-world object or environment, the device may construct its own model (i.e. 3D mesh and UV mapping from that mesh to an unpopulated texture map) from one or more images captured by an image capture module of the device.

When a user moves a capture device relative to real spaces/environments and/or stationary objects, it becomes necessary to refresh virtual content based on the new position of the device. However, the virtual content may not be displayed correctly if the spatial position (i.e. pose) of the device is not tracked accurately. Effective reproduction of virtual content together with real-time, captured video images, therefore, relies upon accurate tracking of the location/orientation of the capture device (i.e. the position of the augmented reality device in space) and near real-time updating of the virtual content. Where augmented reality scenes include both real objects and virtual objects, this requires a tracking that is set and maintained between the real objects and the virtual objects. This tracking is important to maintaining an immersive presentation of the virtual objects within the environment and treating the virtual objects as if they were real within the environment. Failed tracking creates jitter or unexpected movement of the virtual object(s) within a scene, or may set an initial virtual object placement that overlaps or is out of synchronization with real objects in unnatural ways.

One way of tracking the actual location of a device is to start with a highly accurate model of an environment, and to compare the model with image data from a device, frame by frame. Examples of suitable models include the three-dimensional (3D) point cloud model and 3D polygon mesh models discussed above.

Simultaneous location and mapping (SLAM) systems are systems that are used to track key points in two-dimensional image frames of video, and to identify three-dimensional objects from the image frames as well as a relative location of the camera to those objects. Such processing to identify three-dimensional objects, however, is processor and memory intensive.

Rather than using a dense point cloud of complex environment surfaces, embodiments described herein may use compressed or simplified point cloud models of an environment. Such simplified 3D point cloud models may include sets of key point data that follow building edges, environment edges, and surfaces that are stable over time and that present an easily identifiable section in an image. Path edges with high color contrast compared to adjacent surfaces and other fixed objects may be represented in such a simplified point cloud, while typically dynamic objects such as tree branches with leaves or flags may be excluded.

Increasingly, user devices such as smartphones and wearable devices are also provided with one or more inertial measurement unit (IMU) sensors that monitor the orientation and direction of the device (e.g. accelerometers, gyroscopes, etc.). The information from such IMU sensors may be used in conjunction with visual tracking techniques (such as SLAM) to enhance the accuracy of the tracking of the user device in relation to the real objects in the surrounding environment.

Drawings

FIG. 1A is a block diagram showing an example messaging system 100 for exchanging data (e.g., messages and associated content) over a network. The messaging system 100 includes multiple client devices 102, each of which hosts a number of applications including a messaging client application 104. Each messaging client application 104 is communicatively coupled to other instances of the messaging client application 104 and a messaging server system 108 via a network 106 (e.g., the Internet). One or more client companion devices 114 (e.g., wearable devices) may be communicatively connected to one or more of the client devices 102.

Accordingly, each messaging client application 104 is able to communicate and exchange data with another messaging client application 104 and with the messaging server system 108 via the network 106. The data exchanged between messaging client applications 104, and between a messaging client application 104 and the messaging server system 108, includes functions (e.g., commands to invoke functions) as well as payload data (e.g., text, audio, video or other multimedia data).

The messaging server system 108 provides server-side functionality via the network 106 to a particular messaging client application 104. While certain functions of the messaging system 100 are described herein as being performed by either a messaging client application 104 or by the messaging server system 108, it will be appreciated that the location of certain functionality either within the messaging client application 104 or the messaging server system 108 is a design choice. For example, it may be technically preferable to initially deploy certain technology and functionality within the messaging server system 108, but to later migrate this technology and functionality to the messaging client application 104 where a client device 102 has a sufficient processing capacity.

The messaging server system 108 supports various services and operations that are provided to the messaging client application 104. Such operations include transmitting data to, receiving data from, and processing data generated by the messaging client application 104. This data may include, message content, client device information, geolocation information, augmented reality data, media annotation and overlays, message content persistence conditions, social network information, and live event information, as examples. Data exchanges within the messaging system 100 are invoked and controlled through functions available via user interfaces (UIs) of the messaging client application 104. Examples of augmented reality data that may be exchanged using the messaging client application 104 include 3D geometry information corresponding to real and virtual objects.

Turning now specifically to the messaging server system 108, an Application Program Interface (API) server 110 is coupled to, and provides a programmatic interface to, an application server 112. The application server 112 is communicatively coupled to a database server 118, which facilitates access to a database 120 in which is stored data associated with messages processed by the application server 112.

As shown in FIG. 1B, the application server 112 hosts a number of applications and subsystems, including a social network system 122, an engagement tracking system 124, a messaging server application 126, an image processing system 128, and an augmented reality system 162.

Dealing specifically with the Application Program Interface (API) server 110, this server receives and transmits message data (e.g., commands and message payloads) between the client device 102 and the application server 112. Specifically, the Application Program Interface (API) server 110 provides a set of interfaces (e.g., routines and protocols) that can be called or queried by the messaging client application 104 in order to invoke functionality of the application server 112. The Application Program Interface (API) server 110 exposes various functions supported by the application server 112, including account registration, login functionality, the sending of messages, via the application server 112, from a particular messaging client application 104 to another messaging client application 104, the sending of media files (e.g., images or video) from a messaging client application 104 to the messaging server application 126, and for possible access by another messaging client application 104, the setting of a collection of media data (e.g., story), the retrieval of a list of friends of a user of a client device 102, the retrieval of such collections, the retrieval of messages and content, the adding and deletion of friends to a social graph, the location of friends within a social graph, opening and application event (e.g., relating to the messaging client application 104).

The messaging server application 126 implements a number of message processing technologies and functions, particularly related to the aggregation and other processing of content (e.g., textual and multimedia content) included in messages received from multiple instances of the messaging client application 104. The text and media content from multiple sources may be aggregated into collections of content (the collections may be referred to as “stories” or “galleries”, depending upon context and/or content type). These collections are then made available, by the messaging server application 126, to the messaging client application 104. Other processor and memory intensive processing of data may also be performed server-side by the messaging server application 126, in view of the hardware requirements for such processing.

The application server 112 also includes an image processing system 128 that is dedicated to performing various image processing operations, typically with respect to images or video received within the payload of a message at the messaging server application 126. Examples of image processing operations include the upscaling or downscaling of the image data for presentation on a display of a receiving device and the transcoding of the image data for interoperability or compression. The image processing operations may compensate for the differing properties of the individual users' cameras (e.g. exposure) when virtual image content is shared between user devices providing a ‘canonical’ texture for an imaged object. In other instances involving the shared presentation of the same virtual content in different user devices, the virtual content deriving from captured image data from more than one user device, the image processing system 128 may operate to resolve competing views of the same patches of the building—if user A and user B can both see a patch then the server could average their views (after compensating for camera properties), or perhaps reject one of the views, according to an image processing policy.

The social network system 122 supports various social networking functions services, and makes these functions and services available to the messaging server application 126.

The application server 112 is communicatively coupled to a database server 118, which facilitates access to a database 120 in which is stored data associated with messages processed by the messaging server application 126.

The schematic diagram in FIG. 2 shows certain functional blocks illustrating the operation of a client device, according to certain example embodiments.

The client device includes at least one processor and the processor operates to access a UV mapping and a 3D mesh corresponding to a real-world object or environment, operation 202. This may comprise retrieving texture map and a 3D mesh (collectively representing a 3D geometry) from storage means (such as database 120 in communicative connection with application server 112). Alternatively or additionally, the texture map and 3D mesh may be received from a further client device. In certain embodiments, the texture map and 3D mesh may be generated by the client device itself.

In cases where the texture map and 3D mesh are generated by the client device, this operation may be achieved using the technique illustrated in FIG. 3.

In certain example embodiments, the processor may determine the localization of the device relative to the real-world object or environment, operation 204. This initial localization may be used to narrow the scope of the texture map and 3D mesh that the client device needs to access. Examples of techniques for determining an initial localization may include localization of the device by a positioning system of the device (for instance, a positioning hardware module coupled to a storage medium and the at least one processor of the device, the positioning module may be a global positioning system (GPS) module). Alternatively, the user may input a localization directly: for example, inputting a unique identifier (e.g., “Houses of Parliament”), a postal address, grid location in a geographic map or a latitude-longitude pair. In a further alternative, the real-world object or environment may be associated with: an information panel provided with text, signage, a 1-D and/or 2-D barcode data; a radio-frequency identifier (RFID); a near-field communication (NFC) tag; or the like, that the client device may read to determine the localization.

Having determined the initial localization and accessed the texture map and 3D mesh, the processor may execute an operation to track changes in localization of the device relative to the initial localization (and thus, relative to the 3D mesh corresponding to a real-world object or environment). Examples of techniques for tracking changes in localization include the SLAM and IMU techniques mentioned above.

In certain example embodiments, the processor may be placed in a creative mode, during which a user may interact with the client device to introduce a transformation input. The transformation input may, for example, be a user gesture input into the device. The input gesture may be a touch-screen input gesture or a detected change in orientation in an input device while the input device is operated in a gesture input mode. In the latter case, the input device may be embedded within the client device so that changes in orientation and position of the client device tracked by the tracking techniques above may also be used as input gestures.

The processor of the device may, in certain embodiments, generate virtual content by applying a transformation corresponding to the transformation input to the 3D mesh, operation 208. The transformation here maps a plurality of vertices of the 3D mesh to a plurality of transformed vertices in a transformed geometry. The transformed vertices are then populated with texture data according to the mapping and texture data in the texture map.

Finally, at least one current image of the real-world object, captured by an image sensor of the device, may be processed, operation 210, to superpose a view of the virtual content over the current image.

Examples of techniques for superposing virtual content upon images of real-world objects include buffering pixels for each frame of a capture real-world image and replacing selected pixels in each frame by corresponding pixels depicting the virtual content and then presenting the augmented buffered pixels for display. In a further example, suitable for wearable client devices such as smart glasses, the virtual content is presented in an otherwise transparent display layer via a display module of the wearable device.

FIG. 3 illustrates an exemplary technique for generating a texture map and 3D mesh at a client device.

Under the control of a processor of the device, an image sensor of the device is controlled to capture (i.e. photograph) at least one image of a real-world object, operation 302

The processor then determines a 3D geometry corresponding to the real-world object based on the at least one captured image using a conventional photogrammetric technique, operation 304.

The processor then processes the at least one image to extract texture data for respective patches of the object, operation 306.

Finally, a UV mapping is defined from the 3D geometry to a data structure in UV space. In certain embodiments, the data structure is at least partially populated with the extracted texture data, operation 308. The 3D mesh comprises a 3D representation of the respective vertices in the real-world object. The populated data structure is maintained as a texture map.

FIG. 4 illustrates an exemplary technique for tracking changes in localization of a client device. At operation 402, the client device is configured to control an image capture module to capture at least one current image of the real-world object. The at least one current image is processed to identify features (for example straight edges, patches of lighter-than- (or darker-than-)surrounding pixels, etc.), operation 404.

Changes in the location and orientation (in the or each two-dimensional current image) of the identified features are tracked (i.e. measured and stored), operation 406.

The tracked changes in the location and orientation of the identified features are then processed, operation 408, to derive a camera pose (in three dimensions) that, when projected onto a two-dimensional plane best matches the changes in location and orientation of the identified features. Examples of techniques for deriving a camera pose from tracked positions of features identified in captured images include the University of Oxford's PTAM (Parallel Tracking and Mapping) camera tracking system (http://www.robots.ox.ac.uk/˜gk/PTAM/), the FAST corner detection technique (https://www.edwardrosten.com/work/fast.html), SIFT and Ferns (both techniques reviewed in “Pose Tracking from Natural Features on Mobile Phones” by Wagner, D. et al. https://data.icg.tugraz/at/˜dieter/publications/Schmalstieg_142.pdf), the contents of which are each incorporated by reference herein.

FIG. 5 illustrates the application of a transformation on a 3D mesh in accordance with certain example embodiments.

A 3D geometry (corresponding to a real-world object) is represented as a 3D mesh 504 and a corresponding texture map 502. The 3D geometry in FIG. 5 corresponds to a real-world object in the shape of a cube. The cube-shape is used for illustrative purposes only, with no loss of generality: while real-world objects are typically more complex than cubes, the underlying principal illustrated in this Figure remains unchanged.

FIG. 5 shows how any given point on the 3D mesh 504 maps to a corresponding coordinate in the texture map 502. The mapping 512 between 3D mesh 504 and texture map 502 is conventionally referred to as a UV mapping.

When a transformation (here, for example a deformation) is applied to the vertices in the 3D mesh, the resulting 3D geometry is represented as transformed (i.e. deformed) 3D mesh 506. In transformation mapping 514, each point on the deformed 3D mesh 506 maps to a point on the undeformed mesh 504 (and thus indirectly to a coordinate in the texture map 502).

FIG. 6A illustrates the relationship between a real-world object 602, the feed of captured images of that object displayed in a client device 600 and an augmented image displayed in that device in accordance with certain example embodiments.

By accessing (or constructing) a 3D mesh and texture map corresponding to the real-world object (as shown in FIG. 5), the client device can take the current image of the real-world object and generate a transformed, virtual object. The transformation operates on the 3D mesh model derived from the real-world object and, since any given point on the 3D mesh maps to a corresponding coordinate in the texture map 502 (i.e. according to UV mapping 512), a further mapping (i.e. transformation mapping 514) from the unchanged 3D mesh 504 to the transformed 3D mesh 506 effectively permits texture data from the texture map to be mapped onto the transformed 3D mesh 506.

The client device may present different screen-views. In FIG. 6A, these screen-views are represented as displayed screens on a smartphone. A camera image view 606 displays the currently captured video image of the real-world object from the perspective of an integral digital camera. A corresponding texture map 502 includes texture data extracted from visible and unoccluded points of the real-world object (i.e. sides A, B and C of the imaged object).

The texture map 502 may also include pre-existing texture data for some or all points of the object that are currently out of the field of view of the smartphone camera (i.e. sides D, E and F of the imaged object). For objects with permanent foundations in the surrounding environment (such as buildings, bridges etc.), it may safely be assumed that certain aspects of the object are permanently out of view. In certain embodiments, the pre-existing texture data for some or all points of the object may be supplied by reference to a shared texture map for the real-world object and/or the texture map of a second client device having a different perspective upon the object. Pre-existing texture data for some or all points of the object may be accessed from other client devices and/or shared storage servers via the operation of a messaging system such as that illustrated in FIG. 1A.

The client device in FIG. 6A may also present an augmented reality image view 608. Here, the client device displays a virtual view of the transformed 3D mesh 506 and, for each point on the transformed 3D mesh 506 that is in the virtual view, fetches texture data from the texture map 502 according to the UV mapping 512 to points on the original 3D mesh and the transformation mapping 514 from the original points to points in the transformed 3D mesh. It is noted that due to the transformation, counterparts to certain points of the object visible in the camera view are no longer visible in the virtual view.

In certain embodiments, where the original point on the building that corresponds to a deformed point is visible and unoccluded in the current camera feed, the texture data for those visible points may be read directly from the camera feed. Thus, in FIG. 6A, texture data for faces A, B and C are available directly from the camera feed as faces A, B and C are all visible. This provides a more accurate perceived match to the real-world object and a resulting higher quality user experience.

To safeguard against future changes in camera angle and position, the texture data for all points of the object in the currently capture video frame are cached in the texture map 502. Texture data for visible and unoccluded points replaces any pre-existing texture data in the texture map 502.

In certain example embodiments, the replacement of pre-existing texture data is performed gradually in a weighted blending fashion. The accuracy of the pre-existing texture data is thus improved by merging that data with newly captured texture data, so that every pixel in the texture map (or shared texture map) essentially converges over time to a resulting texture data that represents the consensus data for that pixel, given enough views. For each successive frame, the current camera image is assigned a tracking reliability value and this value is then used to weight the blending. For example, frames where the camera is moving a great deal (e.g. detected using IMU sensors such as integrated gyroscope and/or accelerometer) and thus the image can be expected to include a higher level of motion blur than it would at rest are given lower tracking reliability values (as the tracking is likely to be less accurate) and pixels from such frames are given less weight as a result.

FIG. 6B provides a further illustration of the relationship between a real-world object 602, the feed of captured images of that object displayed in a client device 600 and an augmented image displayed in that device in accordance with certain example embodiments.

FIG. 6B illustrates the result of a change 610 in the perspective of the client device from the camera position in which sides A and B are in view to a camera image view 616 where a more limited view of the real-world object (predominantly side C) is available from the perspective of the integral digital camera of the client device 600. Changes in localization and orientation of the client device may be tracked by any of the tracking techniques discussed above.

In this case, the texture data for sides A and B in the texture map 502 may also include texture data cached from previous frames of captured video—captured before the points of the object on sides A and B passed out of the field of view of the smartphone camera.

As a result, the client device 600 in FIG. 6B may also present an augmented reality image view 618. In augmented reality image view 618, the client device displays a virtual view of the transformed 3D mesh 506. As in FIG. 6A, the processor of the client device 600 fetches texture data from the texture map 502 according to the transformation mapping 514 between points on the original 3D mesh 504 and points in the transformed 3D mesh 506, for each point on the transformed 3D mesh 506 that is in the virtual view. In this case, however, certain points of the object are no longer visible in the camera view but counterparts to those points are still visible in the virtual view. The generation of the virtual view includes accessing texture data for points visible in both current camera image view 616 and augmented reality image view 618 directly from the current camera view data and accessing texture data for points visible only in the augmented reality image view 618 by referring to the cached texture data at a corresponding point in the texture map 502. The latter path relies upon the application of both the UV mapping and then the transformation mapping to supply the u,v-coordinate for the texture data for points visible only in the augmented reality image view 618.

While the transformation illustrated in FIGS. 5, 6A and 6B is a uniform deformation of vertical lines into skewed curved lines, the transformation may take many other, often more complicated, forms. Examples of other transformations include replications (in which blocks of the original 3D mesh are replicated at more than one location in the virtual content space and the texture data from the texture map is mapped to vertices in each of the replicated blocks), reflections (in which part or all of the vertices in a 3D mesh are mirrored) and translations (in which part or all of an original 3D mesh is mapped to an undistorted 3D mesh at a spatial offset in virtual content space from the location of the original real-world object). Reflection-type transformations may be used to ensure that signage in the virtual content space remains human-readable while the surrounding virtual content is mirror-reflected.

Caching of texture data is important because it facilitates population of virtual content without requiring heavy use of computational capacity.

In certain embodiments, a dynamic texture map is maintained as a texture cache. The texture map corresponds to a projection of the vertices in a 3D polygonal mesh of a building or other real-world object or environment. The mapping between 3D mesh and texture map might alternatively be referred to as a “UV mapping” as the vertices in the 3D mesh (represented by Cartesian coordinates {x, y, z}) are projected to a two-dimensional map with coordinates{u,v}. The texture cache may be initialized with default texture data, for example, RGBA (0, 0, 0, 0).

As the image capture module of the client device captures frames of video data, the device stores what has been seen by the camera in the current frame at respective pixels of the texture cache.

To perform the caching for a single frame, a 3D mesh that corresponds to the real-world object being imaged is accessed. The 3D mesh is first mapped (i.e. rendered) to the texture cache in UV space (i.e. a UV mapping is generated). For every pixel of the 3D mesh in UV space, the corresponding world position is calculated and then the corresponding coordinates in the current camera image are calculated.

To determine whether the texture data for any given pixel of the 3D mesh in UV space is to be cached (at a corresponding u,v-coordinate), it is determined whether that pixel corresponds to coordinates that are outside of the camera frame. If the coordinates do lie outside of the camera frame there will be no camera image texture data to cache, so these pixels are not cached.

Equally, it is determined whether the surface on which any given pixel of the 3D mesh lies is behind another surface of the 3D mesh from the camera's point of view. If the surface is determined to be behind (i.e. occluded by) another surface, the corresponding camera image pixel will not be the correct surface and again pixels on that occluded surface are not cached.

Determining whether a surface is occluded by another surface may be achieved by first rendering, with depth-buffering, the view-space depths of the original 3D mesh and then checking whether the calculated depth of the pixel in that 3D mesh is equal to the rendered depth (and thus that pixel is indeed on the closest surface to the camera).

If the candidate cached pixel is valid (i.e. within camera frame and one closest surface) then texture data for that pixel is cached in the texture map. In certain embodiments, the texture data may simply replace pre-existing texture data currently stored for that u,v-coordinate. In other embodiments, the texture data may be merged with pre-existing texture data with a low opacity for temporal smoothing. The alpha channel in the RGBA representation of texture data may thus represent how much caching has been done for that pixel.

In many implementations, the image capture devices (e.g. digital cameras integrated in users' smartphones) frequently change their exposure settings depending on the current target image. In certain embodiments, whenever a pixel from the current frame of a given camera image is to be stored in the cache texture/texture map, an exposure compensation function is applied to normalise the current camera exposure before the normalized value is written to storage. As a result, the stored pixel has a color value that has been effectively normalized in brightness. Whenever a pixel is to be retrieved (i.e. the texture data to be read) from the cache texture/texture map, an inverse exposure compensation function is applied to the normalized value in order to match the current camera exposure.

Examples of virtual content effects using the transformation technique described herein include effects in which a mirror image or duplicate of a real-world building may be erected in virtual space and displayed beside the real-world object in an augmented reality screen view.

The transformation technique of the present disclosure may be used to mock-up a cityscape, adding additional levels to apartment blocks and/or replicating existing and placing additional buildings in a virtual view. FIGS. 7A and 7B illustrate a transformation effect in which a new level is inserted in an augmented reality view of a building in accordance with certain embodiments of the present invention. Whereas the camera image view in FIG. 7A shows a building with four rows of windows, the augmented reality screen view in FIG. 7B shows a building with six rows, the lower levels with two rows of windows being duplicated and “inserted” between the existing levels.

The transformation technique of the present disclosure may also be used to pass information between two devices. With a first client device receiving creative input that defines a transformation to be applied to a view of a real-world object (for example, entering text or image information by gesture, touch input or keyboard entry) and generating virtual content that may be shared with another user in a different position relative to the real-world object. FIGS. 8A and 8B illustrate the application of the transformation in accordance with certain embodiments of the present invention to messaging. FIG. 8A shows a camera image view of a building. FIG. 8B illustrates an augmented reality screen-view of the same building with a message “I ♥ N Y” constructed by mapping elements of the fabric of the imaged building to provide the “structure” of the characters in the message.

Software Architecture

FIG. 9 is a block diagram illustrating an example software architecture 906, which may be used in conjunction with various hardware architectures herein described. FIG. 9 is a non-limiting example of a software architecture and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture 906 can be installed on any one or more of the client devices 102 described above.

A representative hardware layer 952 is illustrated and can represent the hardware of a client device such as that illustrated in FIG. 1A. The representative hardware layer 952 includes a processing unit 954 having associated executable instructions 904. Executable instructions 904 represent the executable instructions of the software architecture 906, including implementation of the methods, components and so forth described herein. The hardware layer 952 also includes memory and/or storage modules memory/storage 956, which also have executable instructions 904. The hardware layer 952 may also comprise other hardware 958. A more detailed diagram of a non-limiting example of a machine 1000 implementing the hardware layer is shown in FIG. 10: that machine includes, among other things, processors 1004, memory 1014, and I/O components 1018.

In the example architecture of FIG. 9, the software architecture 906 may be conceptualized as a stack of layers where each layer provides particular functionality. For example, the software architecture 906 may include layers such as an operating system 902, libraries 920 (i.e. a data layer), applications 916 (i.e. an application layer) and a presentation layer 914. Operationally, the applications 916 and/or other components within the layers may invoke application programming interface (API) API calls 908 through the software stack and receive a response as in response to the API calls 908 (i.e. an interface layer). The layers illustrated are representative in nature and not all software architectures have all layers. For example, some mobile or special purpose operating systems may not provide a frameworks/middleware 918, while others may provide such a layer. Other software architectures may include additional or different layers.

The operating system 902 may manage hardware resources and provide common services. The operating system 902 may include, for example, a kernel 922, services 924 and drivers 926. The kernel 922 may act as an abstraction layer between the hardware and the other software layers. For example, the kernel 922 may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services 924 may provide other common services for the other software layers. The drivers 926 are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers 926 include display drivers, camera drivers, inertial measurement unit (IMU) drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration.

The libraries 920 provide a common infrastructure that is used by the applications 916 and/or other components and/or layers. The libraries 920 provide functionality that allows other software components to perform tasks in an easier fashion than to interface directly with the underlying operating system 902 functionality (e.g., kernel 922, services 924 and/or drivers 926). The libraries 920 may include system libraries 944 (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, and the like. In addition, the libraries 920 may include API libraries 946 such as media libraries (e.g., libraries to support presentation and manipulation of various media format such as MPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D in a graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries 920 may also include a wide variety of other libraries 948 to provide many other APIs to the applications 916 and other software components/modules.

The frameworks/middleware 918 (also sometimes referred to as middleware) provide a higher-level common infrastructure that may be used by the applications 916 and/or other software components/modules. For example, the frameworks/middleware 918 may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks/middleware 918 may provide a broad spectrum of other APIs that may be utilized by the applications 916 and/or other software components/modules, some of which may be specific to a particular operating system 902 or platform.

The applications 916 include built-in applications 938 and/or third-party applications 940. Examples of representative built-in applications 938 may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, and/or a game application. Third-party applications 940 may include an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform, and may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or other mobile operating systems. The third-party applications 940 may invoke the API calls 908 provided by the mobile operating system (such as operating system 902) to facilitate functionality described herein. The applications 916 may include an augmented reality client application 942.

The augmented reality application 942 may implement any system or method described herein, including accessing map information, processing image and point cloud data and feature matching, or any other operation described herein. Further, in some embodiments, a messaging application and the augmented reality application 942 may operate together as part of an ephemeral messaging application. Such an ephemeral messaging application may operate to generate images, allow users to add augmented reality elements to the images, and communicate some or all of the images and/or augmented reality data to another system user. After a deletion trigger has been met, the sent data is communicated from the receiving user's system, and may also be synchronized to delete the images and/or augmented reality data from any server involved in communication of the ephemeral message that included the image and/or the augmented reality data. In some embodiments, the trigger for deletion of data from a receiving user's device may be a timer that indicates how long an augmented reality image is displayed for. In other embodiments, the ephemeral messaging system may have set date and time triggers for deletion, or deletion associated with a number of times that a receiving user has accessed the data.

The applications 916 may use built in operating system functions (e.g., kernel 922, services 924 and/or drivers 926), libraries 920, and frameworks/middleware 918 to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems interactions with a user may occur through a presentation layer, such as presentation layer 914. In these systems, the application/component “logic” can be separated from the aspects of the application/component that interact with a user.

FIG. 10 is a block diagram illustrating components of a machine 1000, according to some example embodiments, able to read instructions from a machine-readable medium (e.g., a machine-readable storage medium) and perform any one or more of the methodologies discussed herein. Specifically, FIG. 10 shows a diagrammatic representation of the machine 1000 in the example form of a computer system, within which instructions 1010 (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine 1000 to perform any one or more of the methodologies discussed herein may be executed. As such, the instructions 1010 may be used to implement modules or components described herein. The instructions 1010 transform the general, non-programmed machine 1000 into a particular machine 1000 programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine 1000 operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine 1000 may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine 1000 may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a personal digital assistant (PDA), an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions 1010, sequentially or otherwise, that specify actions to be taken by machine 1000. Further, while only a single machine 1000 is illustrated, the term “machine” shall also be taken to include a collection of machines that individually or jointly execute the instructions 1010 to perform any one or more of the methodologies discussed herein.

The machine 1000 may include processors 1004, memory/storage 1006, and I/O components 1018, which may be configured to communicate with each other such as via a bus 1002. The memory/storage 1006 may include a memory 1014, such as a main memory, or other memory storage, and a storage unit 1016, both accessible to the processors 1004 such as via the bus 1002. The storage unit 1016 and memory 1014 store the instructions 1010 embodying any one or more of the methodologies or functions described herein. The instructions 1010 may also reside, completely or partially, within the memory 1014, within the storage unit 1016, within at least one of the processors 1004 (e.g., within the processor's cache memory), or any suitable combination thereof, during execution thereof by the machine 1000. Accordingly, the memory 1014, the storage unit 1016, and the memory of processors 1004 are examples of machine-readable media.

The I/O components 1018 may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components 1018 that are included in a particular machine 1000 will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components 1018 may include many other components that are not shown in FIG. 10. The I/O components 1018 are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I/O components 1018 may include output components 1026 and input components 1028. The output components 1026 may include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components 1028 may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or other pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like. The input components 1028 may also include one or more image-capturing devices, such as a digital camera for generating digital images and/or video.

In further example embodiments, the I/O components 1018 may include biometric components 1030, motion components 1034, environmental environment components 1036, or position components 1038 among a wide array of other components. For example, the biometric components 1030 may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components 1034 may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environment components 1036 may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometer that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components 1038 may include location sensor components (e.g., a Global Position system (GPS) receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like.

Communication may be implemented using a wide variety of technologies. The I/O components 1018 may include communication components 1040 operable to couple the machine 1000 to a network 1032 or devices 1020 via coupling 1022 and coupling 1024 respectively. For example, the communication components 1040 may include a network interface component or other suitable device to interface with the network 1032. In further examples, communication components 1040 may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices 1020 may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)).

Moreover, the communication components 1040 may detect identifiers or include components operable to detect identifiers. For example, the communication components 1040 may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components 1040, such as, location via Internet Protocol (IP) geo-location, location via Wi-Fi® signal triangulation, location via detecting a NFC beacon signal that may indicate a particular location, and so forth.

The instructions 1010 can be transmitted or received over the network 1032 using a transmission medium via a network interface device (e.g., a network interface component included in the communication components 1064) and utilizing any one of a number of well-known transfer protocols (e.g., HTTP). Similarly, the instructions 1010 can be transmitted or received using a transmission medium via the coupling 1022 (e.g., a peer-to-peer coupling) to devices 1020. The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying the instructions 1010 for execution by the machine 1000, and includes digital or analog communications signals (i.e., carrier signals) or other intangible medium to facilitate communication of such software.

Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.

Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader scope of embodiments of the present disclosure. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single disclosure or inventive concept if more than one is, in fact, disclosed.

The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.

As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present disclosure. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present disclosure as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.

It should also be noted that the present disclosure can also take configurations in accordance with the following numbered clauses:

Clause 1. A computer-implemented method for displaying virtual content in a client device comprising, at a processor of the device: accessing a texture map and a 3D mesh corresponding to a real-world object or environment; determining localization of the device relative to the real-world object or environment; tracking changes in localization of the device; in a creative mode, receiving a transformation input; generating virtual content by applying a transformation corresponding to the transformation input to the 3D mesh, the transformation mapping a plurality of vertices of the 3D mesh to a plurality of transformed vertices in a transformed geometry and populating the transformed vertices with texture data according to the mapping and the texture map; and processing at least one current image of the real-world object, captured by an image sensor of the device, to superpose a view of the virtual content over the current image.

Clause 2. The method of clause 1, wherein accessing a texture map and 3D mesh comprises: capturing, by an image sensor of the device, at least one image of a real-world object; determining a three-dimensional (3D) geometry corresponding to the object based on the at least one captured image; processing the at least one image to extract texture data for respective patches of the object; and populating at least a portion of a data structure for storing texture data, the data structure mapping the texture data to vertices in the 3D geometry, the 3D mesh comprising a 3D representation of the respective vertices in the 3D geometry and the texture map being the populated data structure.

Clause 3. The method of clause 2, further comprising caching the texture data for all vertices in a current camera frame by storing the populated data structure in a storage medium.

Clause 4. The method of clause 3, wherein populating the transformed vertices with texture data comprises: for each transformed vertex, determining whether the vertex of the 3D mesh is visible in the current camera frame; where the vertex of the 3D mesh is visible in the current camera frame, populating the transformed vertex with the texture data extracted at the corresponding visible vertex; and where the vertex of the 3D mesh is not visible in the current camera frame, accessing the populated data structure in the storage medium, obtain cached texture data for the vertex, and populating the transformed vertex with the cached texture data.

Clause 5. The method of any one of clauses 1 to 4, wherein tracking changes in localization of the device comprises: capturing at least one current image of the real-world object; identifying features in the at least one current image; tracking changes in location and orientation of the identified features; and processing the detected changes in localization and orientation of the identified features to generate a real-time camera pose relative to the object.

Clause 6. The method of any one of clauses 1 to 5, wherein the processor is a graphical processor unit (GPU).

Clause 7. The method of any one of clauses 1 to 6, wherein localization of the device is determined by a positioning system of the device.

Clause 8. The method of clause 7, wherein the positioning system comprises at least a first positioning hardware module coupled to a storage medium and the at least one processor of the device.

Clause 9. The method of clause 8, wherein the first positioning hardware module is a global positioning system (GPS) module.

Clause 10. The method of any one of clauses 1 to 9, wherein obtaining the first position estimate comprises receiving a user input position estimate.

Clause 11. The method of any one of clauses 1 to 10, wherein at least one vertex in the 3D mesh maps to two or more transformed vertices in the transformed geometry.

Clause 12. The method of clause 11, wherein the transformation includes a reflection, deformation, duplication, or translation.

Clause 13. The method of clause 11 or clause 12, wherein the transformation corresponds to a user gesture input into the device.

Clause 14. The method of clause 13, wherein the input gesture is a touch-screen input gesture.

Clause 15. The method of clause 13 or clause 14, wherein the input gesture includes a change in orientation in an input device while the input device is operated in a gesture input mode.

Clause 16. The method of any one of clauses 1 to 15, wherein obtaining a texture map and 3D mesh comprises: receiving the texture map and 3D mesh from a second device.

Clause 17. A computer-implemented method for displaying virtual content in a client device comprising, at a processor of the device: obtaining a texture map and a 3D mesh corresponding to a real-world object or environment; determining localization of the device relative to the real-world object or environment; tracking changes in localization of the device; in a sharing mode, receiving transformation information from a source device; generating virtual content by applying a shared transformation corresponding to the transformation information to the 3D mesh, the shared transformation mapping each of the vertices of the 3D mesh to transformed vertices in a transformed geometry and populating the transformed vertices with texture data according to the mapping and the texture map; and processing at least one current image of the real-world object, captured by an image sensor of the device, to superpose a view of the virtual content over the current image.

Clause 18. The method of clause 17, wherein the texture map is stored as a populated data structure in a storage medium in the device, the method further comprising replacing the texture data at vertices in the texture map by current texture data for all vertices visible in a current camera frame.

Clause 19. The method of clause 17 or clause 18, wherein populating the transformed vertices with texture data comprises: for each transformed vertex, determining whether the vertex of the 3D mesh is visible in the current camera frame; where the vertex of the 3D mesh is visible in the current camera frame, populating the transformed vertex with the texture data extracted at the corresponding visible vertex; and where the vertex of the 3D mesh is not visible in the current camera frame, accessing the populated data structure in the storage medium, obtaining cached texture data for the vertex, and populating the transformed vertex with the cached texture data.

Clause 20. A machine-readable medium comprising instructions that, when performed by a device, cause the device to perform a method comprising: obtaining a texture map and a three-dimensional (3D) geometry corresponding to a real 3D structure, the texture map being at least partially populated with texture data, there being a first mapping between points on the 3D geometry and coordinates in the texture map; tracking changes in localization of the device; entering a transformation input state; receiving a transformation input; generating virtual content by applying a transformation corresponding to the transformation input to the 3D geometry, the transformation being a second mapping from a plurality of points in the 3D geometry to a plurality of transformed points in a transformed 3D geometry and populating the transformed points with texture data according to the first and second mappings and the texture map; and processing at least one current image of the real-world object, captured by an image sensor of the device, to superpose a view of the virtual content over the current image.

Clause 21. The non-transitory machine-readable medium of clause 20 comprising further instructions that, when performed by a device, cause the device to perform further method steps of: determining localization of the device relative to the real 3D structure; establishing a communicative connection with an external device; transmitting a request message including information corresponding to the determined localization; and receiving the texture map and the 3D geometry from the external device in accordance with the determined localization.

Clause 22. The non-transitory machine-readable medium of clause 20 or clause 21, wherein obtaining the texture map and the 3D geometry comprises: receiving, from an image sensor of the device, at least one image of the real 3D structure; determining a 3D geometry corresponding to the 3D structure based on the at least one captured image, the 3D geometry comprising a 3D representation of respective points in the 3D structure; processing the at least one image to extract texture data for points of the 3D structure that are visible and not occluded in the at least one image; and populating at least a portion of a data structure with the extracted texture data according to the first mapping, the populated data structure being the texture map.

Claims

1. A computer-implemented method for displaying virtual content in a device comprising: accessing a texture map and a 3D mesh corresponding to a real-world object or environment;identifying a portion of the real-world object or environment that is visible in a current camera feed captured using an image sensor of the device;accessing modified texture data for the portion of the real-world object or environment directly from the current camera feed captured using the image sensor, wherein the modified texture data is created by:assigning a tracking reliability value to each frame captured from the image sensor, each tracking reliability value assigned based on data received by an inertial measurement unit sensor during capture of each frame; andcreating the modified texture data using a weighted blending process, wherein the weights of the weighted blending process are based on the tracking reliability values;replacing texture data associated with the portion of the real-world object or environment in the texture map with the modified texture data;storing the modified texture data in association with the texture map;receiving a transformation input comprising a user gesture input into the device, the user gesture input based on a detected change in an orientation of the device;generating virtual content by applying a transformation corresponding to the transformation input to the 3D mesh, the transformation mapping a plurality of vertices of the 3D mesh to a plurality of transformed vertices in a transformed geometry and populating the transformed vertices with texture data according to the texture map, wherein the transformation comprises at least one of a reflection, a deformation, and a duplication; andprocessing at least one current image of the real-world object or environment, captured using the image sensor of the device, to superpose a view of the virtual content over the at least one current image.

2. The method of claim 1, wherein accessing the texture map and the 3D mesh comprises: capturing, using the image sensor of the device, the at least one current image of the real-world object or environment;determining a three-dimensional (3D) geometry corresponding to the real-world object or environment based on the at least one current image;processing the at least one current image to extract texture data for respective patches of the real-world object or environment; andpopulating at least a portion of a data structure for storing texture data, the data structure mapping the texture data to vertices in the 3D geometry,the 3D mesh comprising a 3D representation of the respective vertices in the 3D geometry and the texture map being the populated data structure.

3. The method of claim 2, further comprising caching the texture data for all vertices in a current camera frame by storing the populated data structure in a storage medium.

4. The method of claim 3, wherein populating the transformed vertices with texture data comprises: for each transformed vertex, determining whether the vertex of the 3D mesh is visible in the current camera frame;where the vertex of the 3D mesh is visible in the current camera frame, populating the transformed vertex with the texture data extracted at a corresponding visible vertex; andwhere the vertex of the 3D mesh is not visible in the current camera frame, accessing the populated data structure in the storage medium, obtain cached texture data for the vertex, and populating the transformed vertex with the cached texture data.

5. The method of claim 1, wherein accessing the texture map and the 3D mesh comprises: determining localization of the device relative to the real-world object or environment; andretrieving the texture map and the 3D mesh from an external device in accordance with the determined localization, the external device being in communicative connection with the device.

6. The method of claim 1, wherein localization of the device is determined by a positioning system of the device.

7. The method of claim 6, wherein the positioning system comprises at least a first positioning hardware module coupled to a storage medium and at least one processor of the device.

8. The method of claim 7, wherein the first positioning hardware module is a global positioning system (GPS) module.

9. The method of claim 1, wherein tracking changes in localization of the device comprises: capturing at least one current image of the real-world object or environment;identifying features in the at least one current image;tracking changes in location and orientation of the identified features; andprocessing the detected changes in localization and orientation of the identified features to generate a real-time camera pose relative to the real-world object or environment.

10. The method of claim 1, wherein at least one vertex in the 3D mesh maps to two or more transformed vertices in the transformed geometry.

11. The method of claim 1, wherein obtaining a texture map and 3D mesh comprises: receiving the texture map and 3D mesh from a second device.

12. The method of claim 1, wherein the transformation comprises a deformation, the deformation comprising a uniform deformation of vertical lines into skewed curved lines.

13. The method of claim 1, wherein the transformation comprises a replication, the replication comprising a replication of at least a portion of the 3D mesh.

14. The method of claim 1, wherein the transformation comprises a reflection, the reflection comprising a reflection of at least some of the plurality of vertices of the 3D mesh.

15. A computer-implemented method for displaying virtual content in a device comprising, at a processor of the device: obtaining a texture map and a 3D mesh corresponding to a real-world object or environment;determining localization of the device relative to the real-world object or environment;identifying a portion of the real-world object or environment that is visible in a current camera feed captured using an image sensor of the device;accessing modified texture data for the portion of the real-world object or environment directly from the current camera feed captured using the image sensor;replacing texture data associated with the portion of the real-world object or environment in the texture map with the modified texture data, wherein the modified texture data is created by:assigning a tracking reliability value to each frame captured from the image sensor, each tracking reliability value assigned based on data received by an inertial measurement unit sensor during capture of each frame; andcreating the modified texture data using a weighted blending process, wherein the weights of the weighted blending process are based on the tracking reliability values;storing the modified texture data in association with the texture map;receiving a transformation input from a source device;generating virtual content by applying a transformation corresponding to the transformation input to the 3D mesh, the transformation mapping a plurality of vertices of the 3D mesh to a plurality of transformed vertices in a transformed geometry and populating the transformed vertices with texture data according the texture map, wherein the transformation comprises at least one of a reflection, a deformation, and a duplication; andprocessing at least one current image of the real-world object or environment, captured using the image sensor, to superpose a view of the virtual content over the at least one current image.

16. The method of claim 15, wherein the texture map is stored as a populated data structure in a storage medium in the device, the method further comprising replacing the texture data at vertices in the texture map by current texture data for all vertices visible in a current camera frame.

17. The method of claim 16, wherein populating the transformed vertices with texture data comprises: for each transformed vertex, determining whether the vertex of the 3D mesh is visible in the current camera frame;where the vertex of the 3D mesh is visible in the current camera frame, populating the transformed vertex with the texture data extracted at a corresponding visible vertex; andwhere the vertex of the 3D mesh is not visible in the current camera frame, accessing the populated data structure in the storage medium, obtaining cached texture data for the vertex, and populating the transformed vertex with the cached texture data.

18. A non-transitory machine-readable medium, comprising instructions that, when performed by a device, cause the device to perform a method comprising: obtaining a texture map and a 3D mesh corresponding to a real-world object, the texture map being at least partially populated with texture data, there being a first mapping between points on the 3D mesh and coordinates in the texture map;identifying a portion of the real-world object or environment that is visible in a current camera feed captured using an image sensor of the device;accessing modified texture data for the portion of the of real-world object or environment directly from the current camera feed captured using the image sensor, wherein the modified texture data is created by:assigning a tracking reliability value to each frame captured from the image sensor, each tracking reliability value assigned based on data received by an inertial measurement unit sensor during capture of each frame; andcreating the modified texture data using a weighted blending process, wherein the weights of the weighted blending process are based on the tracking reliability values;replacing texture data associated with the portion of the real-world object or environment in the texture map with the modified texture data;storing the modified texture data in association with the texture map;entering a transformation input state;receiving a transformation input comprising a user gesture input into the device, the user gesture input based on a detected change in an orientation of the device;generating virtual content by applying a transformation corresponding to the transformation input to the 3D mesh, the transformation mapping a plurality of vertices of the 3D mesh to a plurality of transformed vertices in a transformed geometry and populating the transformed vertices with texture data according to the texture map, wherein the transformation comprises at least one of a reflection, a deformation, and a duplication; andprocessing at least one current image of the real-world object or environment, captured using the image sensor of the device, to superpose a view of the virtual content over the at least one current image.

19. The non-transitory machine-readable medium of claim 18, comprising further instructions that, when performed by a device, cause the device to perform further method steps of: determining localization of the device relative to the real-world object;establishing a communicative connection with an external device;transmitting a request message including information corresponding to the determined localization; andreceiving the texture map and the 3D mesh from the external device in accordance with the determined localization.

20. The non-transitory machine-readable medium of claim 18, wherein obtaining the texture map and the 3D mesh comprises: receiving, from the image sensor, the at least one current image of the real-world object;determining a 3D geometry corresponding to the real-world object based on the at least one current image, the 3D geometry comprising a 3D representation of respective points in the real-world object;processing the at least one current image to extract texture data for points of the real-world object that are visible and not occluded in the at least one current image; andpopulating at least a portion of a data structure with the extracted texture data according to the first mapping, the populated data structure being the texture map.