Point cloud compression for 3d module #23624
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GSoC: Modified PLY reader to support color attribute read/write #23805 * Modified PLY reader to support color attribute read/write * Fix bugs & Modified OBJ reader for color IO * Replace with correct test file * Fix I/O of property [w] in OBJ files ### Pull Request Readiness Checklist **Merged with opencv/opencv_extra#1075 [Issue for GSoC 2023](#23624) The ply loader in 3D module doesn't support color attribute reading. I modified that to support color attribute reading & writing for the color attribute compression as described in proposal. See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
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[GSoC] Update octree methods and create frames for PCC #23985 ## PR for GSoC Point Cloud Compression [Issue for GSoC 2023](#23624) * We are **updating the Octree method create() by using OctreeKey**: Through voxelization, directly calculate the leaf nodes that the point cloud belongs to, and omit the judgment whether the point cloud is in the range when inserted. The index of the child node is calculated by bit operation. * We are also **introducing a new header file pcc.h (Point Cloud Compression) with API framework**. * We added tests for restoring point clouds from an octree. * Currently, the features related to octree creation and point cloud compression are part of the internal API, which means they are not directly accessible to users. However, our plan for the future is to **include only the 'PointCloudCompression' class in the 'opencv2/3d.hpp' header file**. This will provide an interface for utilizing the point cloud compression functionality. The previous PR of this was closed due to repo name conflicts, therefore we resubmitted in this PR. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [x] There is a reference to the original bug report and related work - [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
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Description
The purpose of this issue is to provide a plan outline for the
OpenCV GSoC_2023 Ideas4(Point Cloud Compression). This outline will guide the development of our entire project in order to regulate the development process. Any suggestions will be appreciated!The project is about implementing a point cloud compression algorithm based on the octree. The 3d module in branch 5.x has implemented octree and basic point cloud I/O functions. However, the current octree lacks attributes and functions to realize compression.
A new class will be created in 3d module of branch 5.x to implement all related compression algorithms.
PR Schedule:
Pull requests is planned to be submitted based on the following outline(all PR need code reviews, unit test and documentation):
Refactor relevant code in 3d module:
Implement basic octree compression (Reference: Octree-based Point-Cloud Compression)
Implement compression of color attribute (Reference: Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform)
Further enhancements on compression rate (Reference: G-PCC Codec Description)
Support for dynamic point clouds based on previous efficient algorithms (Reference: Real-time Compression of Point Cloud Streams)
Optimization and formatting
Other References:
H. Liu, H. Yuan, Q. Liu, J. Hou and J. Liu, "A Comprehensive Study and Comparison of Core Technologies for MPEG 3-D Point Cloud Compression," in IEEE Transactions on Broadcasting, vol. 66, no. 3, pp. 701-717, Sept. 2020, doi: 10.1109/TBC.2019.2957652.
Y. Huang, J. Peng, C. . -C. J. Kuo and M. Gopi, "A Generic Scheme for Progressive Point Cloud Coding," in IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 2, pp. 440-453, March-April 2008, doi: 10.1109/TVCG.2007.70441.
Cao, Chao & Preda, Marius & Zaharia, Titus. (2019). 3D Point Cloud Compression: A Survey. 1-9. 10.1145/3329714.3338130.
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