mlsanityData to 7 Oct 2026

Fractional Motion Estimation for Point Cloud Compression

arXiv 2202.00172 ↗First posted 1 Feb 2022eess.IV cs.CVcited by 2

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Abstract (arXiv)

Motivated by the success of fractional pixel motion in video coding, we explore the design of motion estimation with fractional-voxel resolution for compression of color attributes of dynamic 3D point clouds. Our proposed block-based fractional-voxel motion estimation scheme takes into account the fundamental differences between point clouds and videos, i.e., the irregularity of the distribution of voxels within a frame and across frames. We show that motion compensation can benefit from the higher resolution reference and more accurate displacements provided by fractional precision. Our proposed scheme significantly outperforms comparable methods that only use integer motion. The proposed scheme can be combined with and add sizeable gains to state-of-the-art systems that use transforms such as Region Adaptive Graph Fourier Transform and Region Adaptive Haar Transform.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 22 references that are in the map. First posted on arXiv 1 Feb 2022.

Builds on

5 of 22 references.

References · 5

  1. 2015Graph-based compression of dynamic 3D point cloud sequencescited by 15
  2. 2019Predictive Generalized Graph Fourier Transform for Attribute Compression of Dynamic Point Cloudscited by 11
  3. 2018Comments on "Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform"cited by 10
  4. 2020Region adaptive graph fourier transform for 3d point cloudscited by 8
  5. 2020A 3D Motion Vector Database for Dynamic Point Cloudscited by 3

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Citing papers per year: 2022: 1; 2023: 1.

2 papers.