IP Library › Granted Patent US 11,354,840
Granted Patent B2
US 11,354,840 · App. 16/823,328 · Granted Jun 7, 2022

Three dimensional acquisition and rendering

Inventor: Jingyi Yu (Newark, DE)
G06T13/20G06T15/04G06T15/06G06T15/10G06T15/205G06T2200/04G06T2200/08G06V10/462G06V10/758H04N13/204
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Quick Facts
Patent No.
US 11,354,840
App. No.
16/823,328
Granted
Jun 7, 2022
Kind
B2
Abstract

A method and system of using multiple image cameras or multiple image and depth cameras to capture a target object. Geometry and texture are reconstructed using captured images and depth images. New images are rendered using geometry based rendering methods or image based rendering methods.

Claims (64)

1. A method of rendering new images, comprising:

acquiring a set of images using one or more image cameras;

acquiring a set of depth images using one or more depth cameras;

converting the set of depth images to geometric models representing scene objects;

converting the set of images acquired from the one or more image cameras into texture maps; and

rendering new images from the geometric models and texture maps using a geometry-based rendering technique;

wherein converting the depth images to the geometric models comprises:

detecting points in the set of depth images under viewpoint and lighting variations;

generating a descriptor for each point based on its local neighborhood, wherein the descriptor comprises surface normal and specular high light information based on non-lambertian surface assumption applied to the set of depth images;

detecting correspondences across the set of depth images by using the descriptors;

refining, based on the correspondences, camera intrinsic and extrinsic parameters for each image of the set of depth images using bundle-adjustment; and

converting the depth images to the geometric models by using a patch-based multi-view stereo for dense point cloud and a multi-view reconstruction,

wherein converting the set of images acquired from the one or more image cameras into texture maps comprises:

parameterizing the geometric model to divide it into a set of sub-models; and

re-projecting the set of images back to the geometric model to create a new texture map for each of the set of sub-models.

2. The method of claim 1 , wherein the geometry-based rendering technique is rasterization.

3. The method of claim 1 , wherein the geometry-based rendering technique is ray-tracing.

4. The method of claim 1 , wherein the scene object is static and one model and set of textures is converted for that scene object.

5. The method of claim 1 , wherein the scene object is animated.

6. The method of claim 5 , wherein every frame of the animated scene has a separate geometric model and texture map.

7. The method of claim 5 , wherein the animated scene has a single texture map and every frame of the animated scene has a separate geometric model.

8. A system for creating a rendering of images comprising:

one or more processors; and

a memory coupled with the one or more processors, the memory configured to store instructions that when executed by the one or more processors cause the one or more processors to:

acquire a set of images using one or more image cameras;

acquire a set of depth images using one or more depth cameras;

convert the set of depth images to geometric models representing scene objects;

convert the set of images acquired from the one or more image cameras into texture maps; and

render new images from the geometric models and texture maps using a geometry-based rendering technique;

wherein converting the depth images to the geometric models comprises:

detecting points in the set of depth images under viewpoint and lighting variations;

generating a descriptor for each point based on its local neighborhood, wherein the descriptor comprises surface normal and specular high light information based on non-lambertian surface assumption applied to the set of depth images;

detecting correspondences across the set of depth images by using the descriptors;

refining, based on the correspondences, camera intrinsic and extrinsic parameters for each image of the set of depth images using bundle-adjustment; and

converting the depth images to the geometric models by using a patch-based multi-view stereo for dense point cloud and a multi-view reconstruction,

wherein converting the set of images acquired from the one or more image cameras into texture maps comprises:

parameterizing the geometric model to divide it into a set of sub-models; and

re-projecting the set of images back to the geometric model to create a new texture map for each of the set of sub-models.

9. The system of claim 8 , wherein the geometry-based rendering technique is rasterization.

10. The system of claim 8 , wherein the geometry-based rendering technique is ray-tracing.

11. The system of claim 8 , wherein the scene object is static and one model and set of textures is converted for that scene object.

12. The system of claim 8 , wherein the scene object is animated.

13. The system of claim 12 , wherein the scene is animated and every frame of the animated scene has a separate geometric model and texture map.

14. The system of claim 12 , wherein the scene is animated and the animated scene has a single texture map and every frame of the animated scene has a separate geometric model.

15. A non-transitory computer-readable storage medium having stored thereon instructions for causing at least one computer system to create a rendering of images comprising, the instructions comprising:

acquiring a set of images using one or more image cameras;

acquiring a set of depth images using one or more depth cameras;

converting the set of depth images to geometric models representing scene objects;

converting the set of images acquired from the one or more image cameras into texture maps; and

rendering new images from the geometric models and texture maps using a geometry-based rendering technique;

wherein converting the depth images to the geometric models comprises:

detecting points in the set of depth images under viewpoint and lighting variations;

generating a descriptor for each point based on its local neighborhood, wherein the descriptor comprises surface normal and specular high light information based on non-lambertian surface assumption applied to the set of depth images;

detecting correspondences across the set of depth images by using the descriptors;

refining, based on the correspondences, camera intrinsic and extrinsic parameters for each image of the set of depth images using bundle-adjustment; and

converting the depth images to the geometric models by using a patch-based multi-view stereo for dense point cloud and a multi-view reconstruction,

wherein converting the set of images acquired from the one or more image cameras into texture maps comprises:

parameterizing the geometric model to divide it into a set of sub-models; and

re-projecting the set of images back to the geometric model to create a new texture map for each of the set of sub-models.

16. The non-transitory computer-readable storage medium of claim 15 , wherein the geometry-based rendering technique is rasterization.

17. The non-transitory computer-readable storage medium of claim 15 , wherein the geometry-based rendering technique is ray-tracing.

18. The non-transitory computer-readable storage medium of claim 15 , wherein the scene object is static and one model and set of textures is converted for that scene object.

19. The non-transitory computer-readable storage medium of claim 15 , wherein the scene object is animated.

20. The non-transitory computer-readable storage medium of claim 19 , wherein the scene is animated and every frame of the animated scene has a separate geometric model and texture map.

Continuity (4)
Continuation 16004434 · Jun 11, 2018
Continuation PCTUS2016067635 · Dec 19, 2016
Provisional Application 62278269 · Jan 13, 2016
Related Publication 20200219301A1 · Jul 9, 2020