Dynamic Point Cloud Geometry Compression Via Patch-Wise Polynomial Fitting

With the boosting requirements of realistic 3D modeling for immersive applications, advent of the newly developed 3D point cloud has attracted great attention. Frankly, immersive experience using high data volume affirms the importance of efficient compression. Inspired by the video based point cloud compression (V-PCC), we propose a novel point cloud compression algorithm based on polynomial fitting of proper patches. Moreover, the original point cloud is segmented into various patches. We generated corresponding depth maps via projection of all the patches by focusing on geometry information. Instead of directly compressing the absolute values, we utilized proper polynomial functions to fit in each patch to obtain the differences. Finally, it is satisfying to note that the fitting function effectively represents the patch wise geometry information. Moreover, new depth maps are obtained with extremely small and stable values, which are more suitable for video-based compression. Different patch wise fitting parameters are preserved and coded using lossless compression through the open source PAQ project. The proposed approach achieves a noticeable improvement in the compression efficiency while maintaining point cloud quality.