Global Rate-distortion Optimization of Video-based Point Cloud Compression with Differential Evolution




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Peer reviewed



In video-based point cloud compression (V-PCC), one geometry video and one color video are generated from a dynamic point cloud. Then, the two videos are compressed independently using a state-of-the-art video coder. In the Moving Picture Experts Group (MPEG) V-PCC test model, the quantization parameters for a given group of frames are constrained according to a fixed offset rule. For example, for the low-delay configuration, the difference between the quantization parameters of the first frame and the quantization parameters of the following frames in the same group is zero by default. We show that the rate-distortion performance of the V-PCC test model can be improved by lifting this constraint and considering the rate-distortion optimization problem as a multi-variable constrained combinatorial optimization problem where the variables are the quantization parameters of all frames. To solve the optimization problem, we use a variant of the differential evolution algorithm. Experimental results for the low-delay configuration show that our method can achieve a Bj{\o}ntegaard delta bitrate of up to -43.04% and more accurate rate control (average bitrate error to the target bitrate of 0.45% vs. 10.75%) compared to the state-of-the-art method, which optimizes the rate-distortion performance subject to the test model default offset rule. We also show that our optimization strategy can be used to improve the rate-distortion performance of two-dimensional video coders.


Marie Skłodowska-Curie Action Project name: Optimized Dynamic Point Cloud Compression, acronym: OPT-PCC, grant number 836192
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.


Point cloud compression, Rate-distortion optimization, Rate control, Video coding, Differential evolution


Yuan, H., Hamzaoui, R., Neri, F., Yang, S. and Wang, T. (2021) Global rate-distortion optimization of video-based point cloud compression with differential evolution. In: Proc. 23rd International Workshop on Multimedia Signal Processing (IEEE MMSP 2021), Tampere, Oct. 2021.


Research Institute

Institute of Engineering Sciences (IES)