Motion Estimation Techniques for Volumetric Video Attribute Compression

• URL: http://arxiv.org/abs/2607.03576v1
• Date: Fri, 03 Jul 2026 19:36:06 GMT
• Title: Motion Estimation Techniques for Volumetric Video Attribute Compression
• Abstract summary: Point cloud compression relies on techniques to compress both geometry and attributes.<n>This paper proposes a geometry-based inter-coding scheme to compress the attributes of dynamic solid point clouds.<n>An MPEG-free fractional-voxel motion estimation method is proposed to refine motion accuracy to fractional-voxel precision.
• Score: 34.164947762310156
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Point cloud compression relies on techniques to compress both geometry and attributes. Motion-based approaches for dynamic solid point cloud geometry compression within the geometry-based point cloud compression (G-PCC) framework have achieved significant reductions in geometry rate. However, motion-based techniques for attribute compression remain underexplored, making it challenging to achieve significant reductions in the temporal redundancy of attributes. Firstly, this paper proposes a geometry-based inter-coding scheme to compress the attributes of dynamic solid point clouds. Secondly, a graph-based motion-estimation scheme for point-cloud attribute compression is proposed. Thirdly, an interpolation-free fractional-voxel motion estimation method is proposed to refine motion accuracy to fractional-voxel precision. Our experimental results on the MPEG point cloud dataset show that the proposed scheme outperforms G-PCC, GeS-TM, and V-PCC in lossless and lossy geometry conditions. We achieve average bitrate savings of $55.3\%$, $42.3\%$, and $16.5\%$ over G-PCC, GeS-TM, and V-PCC, respectively, under lossy-geometry conditions.

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