The present invention relates to a three-dimensional (3D) space rendering system with multi-camera image depth. More particularly, the invention relates to a 3D space rendering system with multi-camera image depth that uses two smartphones to capture images and that enables rapid establishment of 3D models.
Analytics of 3D spatial information compensates for the deficiencies of two-dimensional spaces and adds a new dimension to planar presentation. An object presented in 3D—be it the interior of a building, a streetscape, or a disaster prevention map—can be visually perceived in a more intuitive manner.
In the matter of model establishment for future digital cities, the construction of a required information architecture can be divided into the modeling of buildings, which is tangible, and the compilation of intangible building attributes. Information for the former can be converted into models by processes involving vector maps, digital images, LiDAR, and/or the point cloud modeling technique.
Once a virtual building or other object takes shape, it can be rendered realistic by texture mapping as well as by direct use of color pictures, with a view to esthetic enhancement and greater ease of identification. The completed 3D model can be effectively used and be considered together with issues like costs and practical needs to facilitate decision-making regarding the degree to which the planned system is to be built.
The present invention provides a 3D space rendering system featuring multi-camera image depth. The system is intended primarily to solve the problem that the popularization and ease of 3D model establishment have been hindered by costly equipment.
The present invention provides a three-dimensional space rendering system with multi-camera image depth, comprising: a headset comprising a body, wherein the body is formed with a first support and a second support; and a 3D software in electrical signal communication with a first image capturing device and a second image capturing device.
Implementation of the present invention at least produces the following advantageous effects:
1. 3D models can be established at low cost; and
2. 3D models can be established rapidly.
The features and advantages of the present invention are detailed hereinafter with reference to the preferred embodiments. The detailed description is intended to enable a person skilled in the art to gain insight into the technical contents disclosed herein and implement the present invention accordingly. In particular, a person skilled in the art can easily understand the objects and advantages of the present invention by referring to the disclosure of the specification, the claims, and the accompanying drawings.
According to an embodiment of the present invention as shown in
The headset 10 is made of a material capable of providing adequate support, such as a paper-based or plastic material. To make the headset 10 out of a paper-based material, referring to
As shown in
The first support 120 is formed on one lateral side of the body 110 and has a first receiving space 121 or a first window 122. The first receiving space 121 is configured for receiving a first image capturing device 31. The first window 122 is configured to enable the lens of the first image capturing device 31 to capture images through the first window 122.
The second support 130 is formed on the opposite lateral side of the body 110 such that the first support 120 and the second support 130 are symmetrically arranged. The second support 130 has a second receiving space 131 or a second window 132. The second receiving space 131 is configured for receiving a second image capturing device 32. The second window 132 is configured to enable the lens of the second image capturing device 32 to capture images through the second window 132.
The first image capturing device 31 and the second image capturing device 32 may be mobile phones with photographic functions and optionally with wireless transmission capabilities.
Apart from supporting the first image capturing device 31 and the second image capturing device 32 respectively, the first support 120 and the second support 130 help fix the distance between, and the directions of, the lenses of the first image capturing device 31 and of the second image capturing device 32 in order to define important parameters of the two image capturing devices 31 and 32 in relation to each other. These parameters form the basis of subsequent computation by the 3D software 20 concerning the first image capturing device 31 and the second image capturing device 32.
Referring to
As shown in
In cases where the first support 120 and the second support 130 are in communication with each other, referring to
Referring to
To apply the foregoing embodiment to the rendering of 3D spaces, referring to
The 3D software 20 is in electrical signal communication with the first image capturing device 31 and the second image capturing device 32 in order to control, and read information from, the first image capturing device 31 and the second image capturing device 32.
The 3D software 20 may be in electrical signal communication with the first image capturing device 31 and the second image capturing device 32 via Bluetooth, WiFi, or NFC. In addition to image information, the 3D software 20 reads from the two image capturing devices 31 and 32 gravity sensor data for calculation of space, GPS data to facilitate calculation of space and positions, and gyroscope detection result to obtain horizontality information of the first image capturing device 31 and of the second image capturing device 32.
To enhance precision of computation, errors associated with the timeline can be controlled to be less than or equal to 50 microseconds (ms). Moreover, the 3D software 20 synchronizes the images of the first image capturing device 31 and of the second image capturing device 32 by calculating the time difference between the clocks of the two image capturing devices 31 and 32 and then correcting the time of the images of the two image capturing devices 31 and 32 accordingly. All the information may be computed in a fog computing system to accelerate the obtainment of 3D information.
The process flow S100 of the 3D software 20 can be divided into two major steps, initializing (S510) and generating full-time-domain images (S610).
The step of initializing (S510) is performed at time point T0 to synchronize image coordinates of at least a T0 first image Img1T0 of the first image capturing device 31 and of at least a T0 second image Img2T0 of the second image capturing device 32 and to generate T0 real-time image coordinates CodeT0 and T0 full-time-domain coordinates FCodeT0. The step of initializing (S510) includes the sub-steps of: acquiring equipment data (S111), synchronizing timeline (S112), performing feature point analysis (S120), comparing minimum-distance features (S130), rendering a real-time 3D image (S140), generating full-time-domain coordinates (S113), and generating a full-time-domain image (S114).
The sub-step of acquiring equipment data (S111) is to acquire the equipment data of the first image capturing device 31 and of the second image capturing device 32. The equipment data may be mobile phone data. More specifically, a database containing mobile phone data of various brands and various models is created in advance, and important parameters of each mobile phone to be used are acquired from the database to facilitate subsequent computation. For example, the equipment data may include the brands, model numbers, lens dimensions, and shell dimensions of the mobile phones to be used and the distance from each lens to the corresponding shell.
The sub-step of synchronizing the timeline (S112) is to synchronize the system timeline of the first image capturing device 31 and of the second image capturing device 32 so as to establish a common basis for subsequent image computation.
The sub-step of performing feature point analysis (S120) is to read the T0 first image Img1T0 of the first image capturing device 31 and the T0 second image Img2T0 of the second image capturing device 32, analyze the feature points (e.g., by Scale-Invariant Feature Transform, SIFT), and generate a plurality of T0 first feature points Img1P(1-X)T0 of the T0 first image and a plurality of T0 second feature points Img2P(1-X)T0 of the T0 second image.
The sub-step of comparing minimum-distance features (S130) is to compare the distances from each of the T0 first feature points Img1P(1-X)T0 to all the T0 second feature points Img2P(1-X)T0 and find the T0 second feature point Img2PXT0 closest to (i.e., having the smallest distance from) any given T0 first feature point Img1PXT0. Each pair of T0 first feature point Img1PXT0 and T0 second feature point Img2PXT0 that are found to have the smallest distance therebetween are determined to be the same feature point, i.e., a T0 real-time common feature point CPXT0. As comparison continues, a plurality of T0 real-time common feature points CP(1-X)T0 are generated. These T0 real-time common feature points CP(1-X)T0 are then used to create T0 real-time image coordinates CodeT0.
The sub-step of comparing minimum-distance features (S130) may carry out feature point matching by the Nearest Neighbor method, and erroneously matched features points can be eliminated by RANSAC. Thus, common objects (i.e., the real-time common feature points CP(1-X)T0) in images captured at the same time by both the first image capturing device 31 and the second image capturing device 32 point are obtained.
After obtaining the T0 real-time common feature points CP(1-X)T0 at T0, distances between corresponding feature points are calculated by a distance calculation method to obtain the depth information of plural objects. The depth information provides parameters for the subsequent rendering sub-step.
In the sub-step of rendering a real-time 3D image (S140), the T0 real-time common feature points CP(1-X)T0 and the T0 real-time image coordinates CodeT0 are used to generate a T0 real-time 3D image 3DT0.
The sub-step of generating T0 full-time-domain coordinates (S113) includes using one of the first image capturing device 31 and the second image capturing device 32 as T0 real-time 3D position information (or more particularly, using the position of the first image capturing device 31 or the second image capturing device 32 at the image capturing moment as the full-time-domain coordinate origin (0, 0, 0)) and cross-referencing the full-time-domain origin to the T0 real-time common feature points CP(1-X)T0 and the T0 real-time image coordinates CodeT0 in order to generate the T0 full-time-domain coordinates FCodeT0 together with the full-time-domain reference point and full-time-domain reference directions of the T0 full-time-domain coordinates FCodeT0.
The sub-step of generating a T0 full-time-domain image (S114) includes incorporating the T0 real-time common feature points CP(1-X)T0 and the T0 real-time 3D image 3DT0 into the T0 full-time-domain coordinates FCodeT0 to generate a T0 full-time-domain image FImagT0.
The step of generating full-time-domain images (S610) includes the sub-steps, to be performed at each time point from time point T1 to time point Tn, of: capturing a Tn image (S110), performing feature point analysis (S120), comparing minimum-distance features (S130), rendering a real-time 3D image (S140), generating Tn full-time-domain coordinates (S150), and generating a Tn full-time-domain image (S160).
The sub-step of capturing a Tn image (S110) uses the first image capturing device 31 and the second image capturing device 32 to capture a Tn first image Img1Tn of the first image capturing device 31 and a Tn second image Img2Tn of the second image capturing device 32 at time point Tn.
The sub-step of performing feature point analysis (S120) is to read the Tn first image Img1Tn and the Tn second image Img2Tn and generate a plurality of Tn first feature points Img1P(1-X)Tn of the Tn first image and a plurality of Tn second feature points Img2P(1-X)Tn of the Tn second image.
The sub-step of comparing minimum-distance features (S130) is to compare the distances from each of the Tn first feature points Img1P(1-X)Tn to all the Tn second feature points Img2P(1-X)Tn and find the Tn second feature point Img2PXTn closest to (i.e., having the smallest distance from) any given Tn first feature point Img1PXTn. Each pair of Tn first feature point Img1PXTn and Tn second feature point Img2PXTn that are found to have the smallest distance therebetween are determined to be the same feature point. As comparison continues, a plurality of Tn real-time common feature points CP(1-X)Tn are generated, followed by Tn real-time image coordinates CodeTn.
In the sub-step of rendering a real-time 3D image (S140), the Tn real-time common feature points CP(1-X)Tn and the Tn real-time image coordinates CodeTn are used to generate a Tn real-time 3D image 3DTn. The sub-step of rendering a real-time 3D image (S140) may involve the use of an extended Kalman filter (EKF) to update the positions and directions of the image capturing devices and to render the image, wherein the image may be a map or a perspective drawing of a specific space, for example.
The sub-step of generating Tn full-time-domain coordinates (S150) is explained as follows. When the first image capturing device 31 and the second image capturing device 32 capture images, there is an overlap 70 between the Tn first image Img1Tn and the Tn−1 first image Img1Tn−1 and also between the Tn second image Img2Tn and the Tn−1 second image Img2Tn−1. Hence, there is an overlap 70 between the Tn real-time common feature points CP(1-X)Tn and the Tn−1 real-time common feature points CP(1-X)Tn−1 and consequently between the Tn real-time 3D image 3DTn and the Tn−1 real-time 3D image 3DTn−1.
Thanks to the foregoing overlap feature, the Tn real-time device position information of the image capturing devices at time point Tn can be cross-referenced to the Tn real-time common feature points CP(1-X)Tn and the Tn real-time image coordinates CodeTn and then integrated with the Tn−1 full-time-domain coordinates FCodeTn−1 at time point Tn−1 to generate Tn full-time-domain coordinates FCodeTn.
The sub-step of generating a Tn full-time-domain image (S160) includes incorporating the Tn real-time common feature points CP(1-X)Tn and the Tn real-time 3D image 3DTn into the Tn full-time-domain coordinates FCodeTn to generate a Tn full-time-domain image FImagTn.
The embodiments described above are intended only to demonstrate the technical concept and features of the present invention so as to enable a person skilled in the art to understand and implement the contents disclosed herein. It is understood that the disclosed embodiments are not to limit the scope of the present invention. Therefore, all equivalent changes or modifications based on the concept of the present invention should be encompassed by the appended claims.
Number | Date | Country | |
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62462547 | Feb 2017 | US |