Fractional Motion Estimation for Point Cloud Compression

TL;DR

This paper introduces a fractional-voxel motion estimation method for point cloud compression, leveraging higher resolution displacements to improve motion compensation over integer-based methods.

Contribution

It proposes a novel fractional-voxel motion estimation scheme tailored for point clouds, enhancing compression efficiency by utilizing fractional displacements.

Findings

Significant performance improvement over integer motion methods.

Compatible with state-of-the-art transform-based compression systems.

Provides more accurate motion compensation for dynamic 3D point clouds.

Abstract

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.