Model-Based Rate-Distortion Optimized Video-Based Point Cloud Compression with Differential Evolution

Yuan, Hui; Hamzamoui, Raouf; Neri, Ferrante; Yang, Shengxiang

Abstract

The Moving Picture Experts Group (MPEG) video-based point cloud compression (V-PCC) standard encodes a dynamic point cloud by first converting it into one geometry video and one color video and then using a video coder to compress the two video sequences. We first propose analytical models for the distortion and bitrate of the V-PCC reference software, where the models’ variables are the quantization step sizes used in the encoding of the geometry and color videos. Unlike previous work, our analytical models are functions of the quantization step sizes of all frames in a group of frames. Then, we use our models and an implementation of the differential evolution algorithm to efficiently minimize the distortion subject to a constraint on the bitrate. Experimental results on six dynamic point clouds show that, compared to the state-of-the-art, our method achieves an encoding with a smaller error to the target bitrate (4.65% vs. 11.94% on average) and a slightly lower rate-distortion performance (on average, the increase in Bjøntegaard delta (BD) distortion is 0.27, and the increase in BD rate is 8.40%).

Citation

Yuan, H., Hamzamoui, R., Neri, F., & Yang, S. (2021, November). Model-Based Rate-Distortion Optimized Video-Based Point Cloud Compression with Differential Evolution. Presented at 11th International Conference, ICIG 2021, Haikou, China

• Presentation Conference Type: Edited Proceedings
• Conference Name: 11th International Conference, ICIG 2021
• Start Date: Nov 26, 2021
• End Date: Nov 28, 2021
• Acceptance Date: Jun 20, 2021
• Online Publication Date: Sep 30, 2021
• Publication Date: Sep 30, 2021
• Deposit Date: Jul 10, 2021
• Publicly Available Date: Oct 1, 2022
• Publisher: Springer Verlag
• Volume: 12888
• Pages: 735-747
• Series Title: Lecture Notes in Computer Science
• Series ISSN: 1611-3349
• Book Title: Image and Graphics
• ISBN: 9783030873547
• DOI: https://doi.org/10.1007/978-3-030-87355-4_61
• Public URL: https://nottingham-repository.worktribe.com/output/5769051
• Publisher URL: https://link.springer.com/chapter/10.1007/978-3-030-87355-4_61
• Related Public URLs: http://icig2021.csig.org.cn/
• Additional Information: Also published as: Image and Graphics; 11th International Conference, ICIG 2021, Haikou, China, August 6–8, 2021, Proceedings, Part I; ; The 11th International Conference on Image and Graphics (ICIG), Haikou, China, postponed from August 6-8, 2021 to November 26–28, 2021.