Patent Application
20200342623
Aspects of the present disclosure relate to object detection and more particularly to long wavelength infrared foveated vision for resolving objects with diminished visibility in a wide field of view for a vehicle.
Objects along a travel path of a vehicle, particularly moving objects, such as animals, that intersect the travel path of the vehicle, are challenging to avoid. Autonomous or semi-autonomous vehicles may include various sensor systems for object detection for driver assistance in avoiding such objects. However, conventional sensor systems often fail in adverse light conditions, including nighttime, low visibility weather (e.g., fog, snow, rain, etc.), glare, and/or the like that obscure or diminish the visibility of such objects. For example, monochromatic sensors generally require active illumination to detect objects in low light conditions and are prone to saturation during glare. As such, objects remain hidden from detection by monochromatic sensors in low light conditions and in the presence of glare, for example, due to external light sources, such as the headlights of other vehicles. Other conventional sensor systems eliminate the need for active illumination by using passive sensors, such as long wavelength infrared sensors. However, such sensor systems typically fail to identify objects in adverse light conditions due to low resolution. Many other conventional sensor systems are cost, weight, and/or size prohibitive for deployment into a vehicle for object detection. Accordingly, objects remain hidden from conventional sensor systems in adverse light conditions, thereby exacerbating the challenge of avoiding such objects. It is with these observations in mind, among others, that various aspects of the present disclosure were conceived and developed.
Implementations described and claimed herein address the foregoing issues by providing systems and methods for object detection. In one implementation, thermal energy data in a long wavelength infrared band for a wide field of view is obtained. The thermal energy data is captured using at least one long wavelength infrared sensor of a sensor suite mounted to a vehicle. A foveated long wavelength infrared image is generated from the thermal energy data. The foveated long wavelength infrared image has a higher resolution concentrated in a designated region of the wide field of view and a lower resolution in a remaining region of the wide field of view. Emissivity and temperature data for the designated region is obtained by processing the foveated long wavelength infrared image. One or more features in the designated region are resolved using the emissivity and temperature data.
In another implementation, a sensor suite is mounted to a vehicle. The sensor suite has a plurality of sensors including at least one long wavelength infrared sensor. The at least one long wavelength infrared sensor captures thermal energy in a long wavelength infrared band for a wide field of view. An image signal processor resolves an object with diminished visibility in the wide field of view using emissivity and temperature data obtained from a foveated long wavelength infrared image. The foveated long wavelength infrared image has a higher resolution concentrated in a designated region of the wide field of view and a lower resolution in a remaining region of the wide field of view. The designated region includes the object.
In yet another implementation, thermal energy data in a long wavelength infrared band for a wide field of view is obtained. A foveated long wavelength infrared image is generated from the thermal energy data. The foveated long wavelength infrared image has a higher resolution concentrated in a designated region of the wide field of view and a lower resolution in a remaining region of the wide field of view. A presence of an object with diminished visibility is detected based on at least one of emissivity or temperature of the thermal energy data exceeding a threshold in the designated region. The object is identified based on a thermal profile generated from the thermal energy data.
Other implementations are also described and recited herein. Further, while multiple implementations are disclosed, still other implementations of the presently disclosed technology will become apparent to those skilled in the art from the following detailed description, which shows and describes illustrative implementations of the presently disclosed technology. As will be realized, the presently disclosed technology is capable of modifications in various aspects, all without departing from the spirit and scope of the presently disclosed technology. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not limiting.
Aspects of the present disclosure provide autonomy for a vehicle in adverse light conditions, such as nighttime, low visibility weather (e.g., fog, snow, rain, etc.), low light conditions, glare, and/or the like that obscure or diminish the visibility of objects. For example, disparate nighttime environments have differing degrees of ambient light, which impacts a sensitivity of a sensor suite of the vehicle used to detect objects. A city environment typically has abundant ambient light from street lamps, adjacent buildings, city congestions, and the like. Meanwhile, a rural environment has limited ambient light that originates primarily from starlight, moonlight, and airglow. In between these environments, a suburban environment has ambient light from street lamps, housing, and vehicular traffic.
Objects may be hidden from detection in the field of view for a vehicle during such adverse light conditions. For example, a mammal, such as a deer, may be not be visible at a side of the street in the dark and dart across the street as the vehicle approaches. Due to the thermal signature of such objects, long wavelength infrared (LWIR) vision permits objects to be detected at various distances from the vehicle in adverse light conditions. However, LWIR typically suffers from a narrow field of view and poor resolution, such that objects may remain hidden from detection depending on where they are located relative to the vehicle. Thus, the presently disclosed technology concentrates resolution of LWIR vision at designated regions in the field of view to detect and identify objects that are otherwise hidden from detection.
By using such LWIR foveated vision, thermal energy for objects may be detected at higher resolution in a designated region of a wide field of view in which hidden objects may be located. Additionally, an extended depth of field may be created to obtain additional detail about the hidden objects in the designated region using multiple LWIR images through stereo vision. The distance to the object is determined by extending a range of distance over which the object remains in focus. Finally, the LWIR foveated vision may be used in combination with other imaging and/or detection systems, including monochromatic sensors, red/green/blue (RGB) sensors, light detection and ranging (LIDAR) sensors, and/or the like for enhanced object detection.
Referring first to
Each of the sensors 104 has a sensor field of view 106 that collectively generate an overall field of view of the external environment in which an object 112 is present. The overall field of view is a wide field of view including a center 110 disposed between extremities 108. The object detection system 100 provides LWIR foveated vision for perception and object resolution in short or long range in adverse light conditions. As shown in
More particularly, the plurality of sensors 104 includes at least one LWIR sensor, which may be married to an RGB sensor and/or other sensors. Each of the sensors 104 may include thin optical elements and a detector, including a digital signal processor (DSP), which converts voltages of the thermal energy captured with the sensors 104 into pixels of thermal energy data, and image signal processor (ISP) that generates the foveated LWIR image 200 from the thermal energy data, and/or the like. In one implementation, each of the sensors 104 are co-boresight, thereby providing enhanced object detection. For example, LWIR sensor(s) may be aligned to a same optical axis as RGB sensor(s) to provide an instantaneous field of view between them. In this case, one pixel in LWIR may map to a two by two grid in RGB, as a non-limiting example, such that one may be downsampled to the resolution of the other. As can be understood from
Generally, the LWIR sensors of the sensors 104 passively capture thermal energy data from which emissivity and temperature of the object 112 may be determined. The emissivity of the surface of a body is its effectiveness in emitting energy as thermal radiation. Infrared emissions from an object are directly related to the temperature of the object. More particularly, emissivity is the ratio, varying from 0 to 1, of the thermal radiation from a surface of an object to the radiation from a perfect black body surface at the same temperature. For example, hotter objects emit more energy in the infrared spectrum than colder objects. Mammals, as well as other moving or static objects of interest, are normally warmer than the surrounding environment. Since targets, such as the object 112, emit more infrared energy than the surrounding environment in the overall field of view, the LWIR sensors capture the thermal energy emitted by the object 112 in the LWIR band, which is ideal for near room temperature objects, and the object detection system 100 detects and identifies the object 112.
Stated differently, due to the emissivity and temperature of the object 112 independent of light conditions in the surrounding environment, the sensors 104 passively capture thermal energy in the LWIR frequency, from which the object 112 may be detected and identified during adverse light conditions. LWIR has a peak temperature value for detection at approximately room temperature, which provides a transmission window for object detection during adverse light conditions, such as nighttime and low visibility weather, such as fog, snow, rain, and/or the like. For example, relative to other frequencies, LWIR provides optimized atmospheric transmission for fog penetration for both advective and radiative fog mediums. Additionally, due to the emissivity of targets, such as the object 112, the sensors 104 may capture thermal energy data for the object 112 at near distances from the vehicle, as well as far distances from the vehicle, for example, at a range of approximately 200 meters.
Capturing thermal energy data in the LWIR band enables the object detection system 100 to resolve targets, such as the object 112, in various imaging applications. For example, the object detection system 100 may use the thermal energy data in the LWIR frequency in: thermal emission contrasting, for example, to generate a high contrast image distinguishing between hotter and colder objects; obstacle detection distinguishing between those objects which may be an obstacle along a travel path of the vehicle and those that are not; daytime image contrasting to perceive objects in more detail that appear saturated when observed using other sensors 104, such as a RGB sensor (e.g., using a composite of an RGB image and a LWIR image); and anti-glare applications to perceive objects obscured by glare, for example, originating from headlights of oncoming traffic, reflections of sunlight off surfaces, and/or other light sources.
Despite the obvious advantages of LWIR sensing, LWIR is not conventionally utilized in object detection, as it generally is low resolution and has a narrow field of view. Thus, the sensor suite 102 combines higher resolution sensors with lower resolution sensors to generate a wide field of view, and one or more ISPs concentrates the higher resolution at the designated region 202 to detect and identify the object 112 located therein. Stated differently, the sensor suite 102 includes a multi-sensor configuration enabling autonomy in adverse light conditions by capturing thermal energy in the LWIR band and compensating for a lack of spatial resolution in LWIR through a foveated approach.
The sensor suite 102 thereby acquires wide field of view and high dynamic range LWIR images with high-resolution concentrated in region(s) of the field of view where targets may be present. While field of view, resolution, and depth of field of conventional sensors are limited according to the corresponding optics, a foveated approach overlaps the sensor field of view 106 of one or more of the sensors 104 to capture a wide visual field with a dynamically embedded, high-resolution designated region 202. In one implementation, peripheral sensors of the sensors 104 disposed at the extremities 108 of the wide field of view capture context for detection and tracking of the object 112 in lower resolution, and foveated sensors of the sensors 104 located at the center 110 of the wide field of view provide a resolution many magnitudes greater than the peripheral sensors, thereby capturing the fine details for recognition and detailed examination of the object 112. Stated differently, the ISP(s) of the object detection system 100 generate the foveated LWIR image 200 through image processing in which the image resolution, or amount of detail, varies across the foveated LWIR image 200 according to one or more fixation points associated with the designated region 202. The fixation points thus indicate the highest resolution region of the foveated LWIR image 200. The fixation points may be configured automatically, for example, based on the relationship of the sensor field of views 106 and/or the optics of the sensors 104.
In one implementation, the sensors 104 include a plurality of SEFL lenses to provide a longer depth of field and at least one LEFL lens to provide a foveated approach. As such, the object detection system 100 directs higher resolution to the designated region 202, which in the example shown in
In one implementation, the object detection system 100 determines that the object 112 is moving based on a change in a location or intensity of the emissivity and temperature values from the foveated LWIR image 200 to a second foveated LWIR image. Stated different, as the object 112 moves, the sensor suite 102 will capture thermal energy data corresponding to different locations within the field of view, resulting in a change between image frames. In addition or alternative to detecting a change between image frames, the object detection system 100 detects an object within the field of view based on temperature and emissivity data. More particularly, the object detection system 100 processes the foveated LWIR image 200 to obtain emissivity and temperature data within the designated region 202 from which a thermal profile for the object 112 may be generated.
More particularly, the ISP directs the higher resolution to the designated region 202 and generates the thermal profile for the object 112 based on the emissivity and temperature within the designated region 202. The thermal profile indicates a presence of the object 112 in the designated region 202. After such detection of the object 112, the object detection system 100 identifies the object 112. In one implementation, the object detection system 100 stores or otherwise obtains reference thermal profiles for a variety of objects at different distances, and through a comparison of the thermal profile for the object 112 with the reference thermal profiles, the object 112 is identified. For example, a pedestrian at a particular distance may exhibit certain thermal characteristics distinguishable from a pedestrian at another particular distance and from other object types, such that various thermal profiles for different objects at different distances may be generated for object identification and ranging. In another implementation, the sensor suite 102 is thermally calibrated with the reference thermal profiles or trained via machine learning to recognize a thermal profile of an object at a particular distance for object identification and ranging. For each pixel, a response of the thermal energy data captured by the sensors 104 will behave as a function of temperature, such that a thermal profile for the object 112 may be generated and analyzed to determine an object type of the object 112 and a distance of the object 112 from the vehicle. Because it is known where the higher resolution is in the designated region 202 and where the lower resolution is in the remaining region 204, a different amount of pixels may be used to identify and detect objects located at the center 110 than the extremities 108.
In identifying the object 112 using the thermal profile, in one implementation, the object detection system 100 analyzes a relationship of temperature and/or emissivity of the object 112 with a size of the object 112, a distance to the object 112, and/or the like. The thermal profile may include thermal parameters including emissivity, temperature, size, distance, and/or the like, which may be compared to reference parameters stored to provide different levels of discrimination of object identification. The object detection system 100 thus provides a fine tuned but coarse level resolution of hidden features in a wide field of view based on emissivity and temperature data.
In one example, the object detection system 100 may be used to perceive hidden features of the object 112 that are obscured by glare. For example, light may be emitted from headlights at the center 110 of the field of view, such that the object 112 has diminished visibility. While any RGB sensors or similar sensors of the sensor suite 102 will saturate in such adverse light conditions, the LWIR sensors provide an anti-glare approach. The RGB sensor, for example, includes a full well of a certain number of electrons, and at certain pixels the full well saturates in RGB in the presence of glare. On the other hand, LWIR provides a higher dynamic range. For example, headlights of vehicles are typically light emitting diode (LED) based or incandescent based, such that headlights are constrained to a certain frequency on the thermal spectrum. As such, the LWIR sensor not only does not saturate as a flux of thermal energy in watts per square meter is received through the dedicated aperture, the LWIR sensor is able to distinguish between the thermal profile of the headlights and the thermal profile of the object 112, thereby resolving hidden features of the object 112 that were otherwise obscured by the glare.
As described herein, the designated region may be at various locations within the field of view depending on where objects may have diminished visibility, and using programmable foveated LWIR vision. As shown in
Turning to
Each of the sensors 304 has a sensor field of view 306 that collectively generate an overall field of view of the external environment in which an object 312 is present. The overall field of view is a wide field of view including a center 310 disposed between extremities 308. The object detection system 300 provides LWIR foveated vision for perception and object resolution in short or long range in adverse light conditions. As shown in
As an example, the vehicle may be traveling along a travel path at night in a rural environment where the headlights may not illuminate the object 312 since it is located at the extremities 308 of the field of view. Using the foveated LWIR vision, the object detection system 300 detects the presence of the object 312 at the extremities 308, and identifies the object type of the object 312 (e.g., a deer) and a distance to the object 312. In one implementation, the object detection system 300 communicates the detection and identification of the object 312 to a vehicle controller of the vehicle which executes at least one vehicle operation in response. The vehicle operation may include, without limitation, presenting a notification of a presence of the object; controlling a direction of travel of the vehicle to avoid the object; slowing a speed of the vehicle; directing at least one light source towards the designated region to illuminate the object 312; and/or the like. For example, the notification may be a visual, audial, and/or tactile alert presented to a driver of the vehicle using a user interface. In one example, the object 312 is highlighted using a heads-up display (HUD) or via an augmented reality interface. The light source may be directed towards the object 312 through a cueing approach.
Conventionally, object detection systems have a field of view that suffers from low-resolution and degradation at edges where objects, such as mammals, pedestrians, and/or the like may be present. Thus, the foveated approach described with respect to
Turning to
For example,
For a detailed description of LWIR foveated vision with an extended depth of field, which brings into focus targets that may have been mis-detected using a single sensor or for which otherwise additional detail, including distance, is needed, reference is made to
As shown in
To determine whether the pixels in the grid 1404 correspond to the same object with a horizontal disparity or different objects, the fused image is multiplied with a matrix of unique detection features to determine how similar the fused image is to reference thermal parameters, such as emissivity and temperature, indicating what an object is as a function of distance. Using this information, the ISP(s) confirm whether the object is the same across the images 1204-1206 and resolve the horizontal disparity based on the known distance between the corresponding LWIR apertures to provide a resolved image and distance to the object through stereo processing. Thus, in addition to spatial resolution, the presently disclosed technology is providing different perspectives to resolve objects at different depths.
In one implementation, an operation 1404 generates a foveated long wavelength infrared image from the thermal energy data. The foveated long wavelength infrared image has a higher resolution concentrated in a designated region of the wide field of view and a lower resolution in a remaining region of the wide field of view. For example, the designation region may include extremities of the wide field of view and the remaining region may include a center of the wide field of view. In another example, the designation region includes a center of the wide field of view and the remaining region includes extremities of the wide field of view.
An operation 1406 obtains emissivity and temperature data for the designated region by processing the foveated long wavelength infrared image, and an operation 1408 resolves one or more hidden features in the designated region using the emissivity and temperature data. The one or more hidden features may correspond to an object obscured by glare, an object with diminished visibility caused by adverse light conditions, and/or the like. In one implementation, the operation 1408 determines that the one or more hidden features correspond to a moving object based on a change in the emissivity and temperature data from the foveated long wavelength infrared image to a second foveated long wavelength infrared image. In another implementation, the operation 1408 detects and identifies an object in the designated region. The object may be identified based on a thermal profile generated from the emissivity and temperature data. For example, the object may be identified through a comparison of the thermal profile with one or more reference thermal profiles. Alternatively or additionally, the object may be identified by discriminating the emissivity and temperature data according to a relationship of at least one of emissivity or temperature with distance.
In one implementation, an extended depth of field is generated for the one or more hidden features. For example, the extended depth of field may be generated by fusing the foveated long wavelength infrared image with a second foveated long wavelength infrared image. The second foveated long wavelength infrared image represents a perspective and a distance to the one or more hidden features that are different from the first foveated long wavelength infrared image.
Turning to
In one implementation, the electronic device 1500 includes a display unit 1502 to display information, such as a graphical user interface, and a processing unit 1504 in communication with the display unit 1502 and an input unit 1506 to receive data from one or more input devices or systems, such as the various sensor suites described herein. Various operations described herein may be implemented by the processing unit 1504 using data received by the input unit 1506 to output information for display using the display unit 1502.
Additionally, in one implementation, the electronic device 1500 includes a generation unit 1508, a detection unit 1510, and an identification unit 1512. The input unit 1506 obtains thermal energy data in a long wavelength infrared frequency for a wide field of view. The generation unit 1508 generates a foveated long wavelength infrared image from the thermal energy data. The foveated long wavelength infrared image has a higher resolution concentrated in a designated region of the wide field of view and a lower resolution in a remaining region of the wide field of view. The detection unit 1510 detects a presence of an object with diminished visibility based on emissivity and/or temperature of the thermal energy data exceeding a threshold in the designated region. The identification unit 1512 identifies the object based on a thermal profile generated from the thermal energy data. In another implementation, the electronic device 1500 includes units implementing the operations described with respect to
Referring to
The computer system 1600 may be a computing system is capable of executing a computer program product to execute a computer process. Data and program files may be input to the computer system 1600, which reads the files and executes the programs therein. Some of the elements of the computer system 1600 are shown in
The processor 1602 may include, for example, a central processing unit (CPU), a microprocessor, a microcontroller, a digital signal processor (DSP), and/or one or more internal levels of cache. There may be one or more processors 1602, such that the processor 1602 comprises a single central-processing unit, or a plurality of processing units capable of executing instructions and performing operations in parallel with each other, commonly referred to as a parallel processing environment.
The computer system 1600 may be a conventional computer, a distributed computer, or any other type of computer, such as one or more external computers made available via a cloud computing architecture. The presently described technology is optionally implemented in software stored on the data stored device(s) 1604, stored on the memory device(s) 1606, and/or communicated via one or more of the ports 1608-1612, thereby transforming the computer system 1600 in
The one or more data storage devices 1604 may include any non-volatile data storage device capable of storing data generated or employed within the computing system 1600, such as computer executable instructions for performing a computer process, which may include instructions of both application programs and an operating system (OS) that manages the various components of the computing system 1600. The data storage devices 1604 may include, without limitation, magnetic disk drives, optical disk drives, solid state drives (SSDs), flash drives, and the like. The data storage devices 1604 may include removable data storage media, non-removable data storage media, and/or external storage devices made available via a wired or wireless network architecture with such computer program products, including one or more database management products, web server products, application server products, and/or other additional software components. Examples of removable data storage media include Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc Read-Only Memory (DVD-ROM), magneto-optical disks, flash drives, and the like. Examples of non-removable data storage media include internal magnetic hard disks, SSDs, and the like. The one or more memory devices 1606 may include volatile memory (e.g., dynamic random access memory (DRAM), static random access memory (SRAM), etc.) and/or non-volatile memory (e.g., read-only memory (ROM), flash memory, etc.).
Computer program products containing mechanisms to effectuate the systems and methods in accordance with the presently described technology may reside in the data storage devices 1604 and/or the memory devices 1606, which may be referred to as machine-readable media. It will be appreciated that machine-readable media may include any tangible non-transitory medium that is capable of storing or encoding instructions to perform any one or more of the operations of the present disclosure for execution by a machine or that is capable of storing or encoding data structures and/or modules utilized by or associated with such instructions. Machine-readable media may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more executable instructions or data structures.
In some implementations, the computer system 1600 includes one or more ports, such as an input/output (I/O) port 1608, a communication port 1610, and a sub-systems port 1612, for communicating with other computing, network, or vehicle devices. It will be appreciated that the ports 1608-1612 may be combined or separate and that more or fewer ports may be included in the computer system 1600.
The I/O port 1608 may be connected to an I/O device, or other device, by which information is input to or output from the computing system 1600. Such I/O devices may include, without limitation, one or more input devices, output devices, and/or environment transducer devices.
In one implementation, the input devices convert a human-generated signal, such as, human voice, physical movement, physical touch or pressure, and/or the like, into electrical signals as input data into the computing system 1600 via the I/O port 1608. Similarly, the output devices may convert electrical signals received from computing system 1600 via the I/O port 1608 into signals that may be sensed as output by a human, such as sound, light, and/or touch. The input device may be an alphanumeric input device, including alphanumeric and other keys for communicating information and/or command selections to the processor 1602 via the I/O port 1608. The input device may be another type of user input device including, but not limited to: direction and selection control devices, such as a mouse, a trackball, cursor direction keys, a joystick, and/or a wheel; one or more sensors, such as a camera, a microphone, a positional sensor, an orientation sensor, a gravitational sensor, an inertial sensor, and/or an accelerometer; and/or a touch-sensitive display screen (“touchscreen”). The output devices may include, without limitation, a display, a touchscreen, a speaker, a tactile and/or haptic output device, and/or the like. In some implementations, the input device and the output device may be the same device, for example, in the case of a touchscreen.
The environment transducer devices convert one form of energy or signal into another for input into or output from the computing system 1600 via the I/O port 1608. For example, an electrical signal generated within the computing system 1600 may be converted to another type of signal, and/or vice-versa. In one implementation, the environment transducer devices sense characteristics or aspects of an environment local to or remote from the computing device 1600, such as, light, sound, temperature, pressure, magnetic field, electric field, chemical properties, physical movement, orientation, acceleration, gravity, and/or the like. Further, the environment transducer devices may generate signals to impose some effect on the environment either local to or remote from the example computing device 1600, such as, physical movement of some object (e.g., a mechanical actuator), heating or cooling of a substance, adding a chemical substance, and/or the like.
In one implementation, a communication port 1610 is connected to a network by way of which the computer system 1600 may receive network data useful in executing the methods and systems set out herein as well as transmitting information and network configuration changes determined thereby. Stated differently, the communication port 1610 connects the computer system 1600 to one or more communication interface devices configured to transmit and/or receive information between the computing system 1600 and other devices by way of one or more wired or wireless communication networks or connections. Examples of such networks or connections include, without limitation, Universal Serial Bus (USB), Ethernet, Wi-Fi, Bluetooth®, Near Field Communication (NFC), Long-Term Evolution (LTE), and so on. One or more such communication interface devices may be utilized via the communication port 1610 to communicate one or more other machines, either directly over a point-to-point communication path, over a wide area network (WAN) (e.g., the Internet), over a local area network (LAN), over a cellular (e.g., third generation (3G), fourth generation (4G), or fifth generation (5G)) network, or over another communication means. Further, the communication port 1610 may communicate with an antenna or other link for electromagnetic signal transmission and/or reception. In some examples, an antenna may be employed to receive Global Positioning System (GPS) data to facilitate determination of a location of a machine, vehicle, or another device.
The computer system 1600 may include a sub-systems port 1612 for communicating with one or more systems related to a vehicle to control an operation of the vehicle and/or exchange information between the computer system 1600 and one or more sub-systems of the vehicle. Examples of such sub-systems of a vehicle, include, without limitation, imaging systems, radar, LIDAR, motor controllers and systems, battery control, fuel cell or other energy storage systems or controls in the case of such vehicles with hybrid or electric motor systems, autonomous or semi-autonomous processors and controllers, steering systems, brake systems, light systems, navigation systems, environment controls, entertainment systems, and the like.
In an example implementation, object detection information, reference thermal profiles, calibration data, and software and other modules and services may be embodied by instructions stored on the data storage devices 1604 and/or the memory devices 1606 and executed by the processor 1602. The computer system 1600 may be integrated with or otherwise form part of a vehicle. In some instances, the computer system 1600 is a portable device that may be in communication and working in conjunction with various systems or sub-systems of a vehicle.
The present disclosure recognizes that the use of such information may be used to the benefit of users. For example, the location information of a vehicle may be used to provide targeted information concerning a “best” path or route to the vehicle and to avoid objects. Accordingly, use of such information enables calculated control of an autonomous vehicle. Further, other uses for location information that benefit a user of the vehicle are also contemplated by the present disclosure.
Users can selectively block use of, or access to, personal data, such as location information. A system incorporating some or all of the technologies described herein can include hardware and/or software that prevents or blocks access to such personal data. For example, the system can allow users to “opt in” or “opt out” of participation in the collection of personal data or portions thereof. Also, users can select not to provide location information, or permit provision of general location information (e.g., a geographic region or zone), but not precise location information.
Entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal data should comply with established privacy policies and/or practices. Such entities should safeguard and secure access to such personal data and ensure that others with access to the personal data also comply. Such entities should implement privacy policies and practices that meet or exceed industry or governmental requirements for maintaining the privacy and security of personal data. For example, an entity should collect users' personal data for legitimate and reasonable uses and not share or sell the data outside of those legitimate uses. Such collection should occur only after receiving the users' informed consent. Furthermore, third parties can evaluate these entities to certify their adherence to established privacy policies and practices.
The system set forth in
In the present disclosure, the methods disclosed may be implemented as sets of instructions or software readable by a device. Further, it is understood that the specific order or hierarchy of steps in the methods disclosed are instances of example approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the method can be rearranged while remaining within the disclosed subject matter. The accompanying method claims present elements of the various steps in a sample order, and are not necessarily meant to be limited to the specific order or hierarchy presented.
The described disclosure may be provided as a computer program product, or software, that may include a non-transitory machine-readable medium having stored thereon instructions, which may be used to program a computer system (or other electronic devices) to perform a process according to the present disclosure. A machine-readable medium includes any mechanism for storing information in a form (e.g., software, processing application) readable by a machine (e.g., a computer). The machine-readable medium may include, but is not limited to, magnetic storage medium, optical storage medium; magneto-optical storage medium, read only memory (ROM); random access memory (RAM); erasable programmable memory (e.g., EPROM and EEPROM); flash memory; or other types of medium suitable for storing electronic instructions.
While the present disclosure has been described with reference to various implementations, it will be understood that these implementations are illustrative and that the scope of the present disclosure is not limited to them. Many variations, modifications, additions, and improvements are possible. More generally, embodiments in accordance with the present disclosure have been described in the context of particular implementations. Functionality may be separated or combined in blocks differently in various embodiments of the disclosure or described with different terminology. These and other variations, modifications, additions, and improvements may fall within the scope of the disclosure as defined in the claims that follow.
The present application claims priority to U.S. Provisional Application No. 62/837,609, entitled “Systems and Methods for Resolving Hidden Features in a Field of View” and filed on Apr. 23, 2019, which is incorporated by reference herein in its entirety.
| Number | Date | Country | |
|---|---|---|---|
| 62837609 | Apr 2019 | US |
