Surface normal vector processing mechanism

Patent metadata

Field	Value
Publication number	US-11284118-B2
Application number	US-202017111677-A
Country	US
Kind code	B2
Filing date	Dec 4, 2020
Priority date	Jul 31, 2018
Publication date	Mar 22, 2022
Grant date	Mar 22, 2022

Abstract

An apparatus to facilitate processing video bit stream data is disclosed. The apparatus includes one or more processors to encode surface normals data with point cloud geometry data included in the video bit stream data for reconstruction of objects within the video bit stream data based on the surface normals data and a memory communicatively coupled to the one or more processors.

First claim

What is claimed is:

1. An apparatus to facilitate processing video bit stream data, comprising:
one or more processors to encode surface normals data with point cloud geometry data included in the video bit stream data for reconstruction of objects within the video bit stream data by using the surface normals data to apply lighting models to perform subjective artifact reduction to identify each of a plurality of separate objects in the video bit stream, wherein three-dimensional the surface normals data is encoded within the point cloud geometry data via a plurality color components of color component data and video metadata is encoded to indicate that the color component data includes the three-dimensional surface normals data; and
a memory communicatively coupled to the one or more processors.

2. The apparatus of claim 1 , wherein encoding the surface normals data with the point cloud geometry data comprises encoding a vector perpendicular to each point on a surface of an object to provide directions associated with the object.

3. The apparatus of claim 2 , wherein the one or more processors further to encode the surface normals data via a high level syntax to indicate that surface normals data is included within the video bit stream.

4. The apparatus of claim 3 , wherein the video bit stream is encoded using a High Efficiency Video Coding (HEVC) coding.

5. The apparatus of claim 4 , wherein the one or more processors further to encode the surface normals data within HEVC color component data.

6. The apparatus of claim 1 , wherein the metadata comprises HEVC video usability information (VUI) metadata.

7. The apparatus of claim 6 , wherein the metadata comprises HEVC video parameter set (VPS) data.

8. An apparatus to facilitate processing video bit stream data, comprising:
one or more processors to receive surface normals data encoded within point cloud geometry data included in the video bit stream data and reconstruct objects within the video bit stream data by using the surface normals data to apply lighting models to perform subjective artifact reduction to identify each of a plurality of separate objects in the video bit stream, wherein three-dimensional the surface normals data is encoded within the point cloud geometry data via a plurality color components of color component data and video metadata is encoded to indicate that the color component data includes the three-dimensional surface normals data; and
a memory communicatively coupled to the one more processors.

9. The apparatus of claim 8 , wherein reconstructing the objects within the video bit stream data based on the surface normals comprises rendering the object using the directions provided with the vector for each point on the surface of the object.

10. The apparatus of claim 9 , wherein the one or more processors further to decode the surface normals data via a high level syntax to indicate that surface normals data is included within the video bit stream and render the object using the directions provided with the vector for each point on the surface of the object.

11. The apparatus of claim 10 , wherein the surface normals data is decoded using a High Efficiency Video Coding (HEVC) coding.

12. The apparatus of claim 11 , wherein the surface normals data is decoded within HEVC color component data.

13. The apparatus of claim 11 , wherein the metadata comprises HEVC video usability information (VUI) metadata.

14. The apparatus of claim 8 , wherein the one or more processors further to extract surface normals from a depth map for approximations.

15. The apparatus of claim 14 , wherein performing the approximations comprises determining a differentiation vector between two horizontal pixels and vertical pixels on a surface, calculating a Ground Sample Distance (GSD) of a pixel and approximating a horizontal distance between two neighboring pixels as the GSD.

16. A method to facilitate processing video bit stream data, comprising:
receiving the video bit stream data; and
encoding surface normals data with point cloud geometry data for reconstruction of objects within the video bit stream data by using the surface normals data to apply lighting models to perform subjective artifact reduction to identify each of a plurality of separate objects in the video bit stream, wherein three-dimensional the surface normals data is encoded within the point cloud geometry data via a plurality color components of color component data and video metadata is encoded to indicate that the color component data includes the three-dimensional surface normals data.

17. The method of claim 16 , wherein encoding the surface normals data with the point cloud geometry data comprises encoding a vector perpendicular to each point on a surface of an object to provide directions associated with the object.

18. The method of claim 17 , wherein encoding the surface normals data further comprises encoding the surface normals data via a high level syntax to indicate that surface normals data is included within the video bit stream.

19. The method of claim 17 , wherein encoding the surface normals data further comprises encoding the surface normals data within color component data.

20. The method of claim 19 , wherein encoding the surface normals data further comprises encoding metadata to indicate that the HEVC color component data includes surface normals data.

Assignees

• Intel Corp

Inventors

• Boyce Jill
• Janus Scott
• Kaufman Itay
• Sharma Archie
• Baran Stanley
• Apodaca Michael
• Surti Prasoonkumar
• Potluri Srikanth
• Das Barnan
• Labbe Hugues
• Oh Jong Dae
• Cilingir Gokcen
• Bortman Maria
• Ashkenazi Tzach
• Distler Jonathan
• Divekar Atul
• Varerkar Mayuresh M
• Biswal Narayan
• Shah Nilesh V
• Kuwahara Atsuo
• Xiao Kai
• Tanner Jason
• Tripp Jeffrey

Classifications

• G06T15/005 Primary

  General purpose rendering architectures · CPC title

• H04N21/816

  involving special video data, e.g 3D video · CPC title

• G06T1/20

  Processor architectures; Processor configuration, e.g. pipelining · CPC title

• G06T9/00

  Image coding (bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00) · CPC title

• G06T2207/10028

  Range image; Depth image; 3D point clouds · CPC title