Ultron: Enabling Temporal Geometry Compression of 3D Mesh Sequences using Temporal Correspondence and Mesh Deformation

TL;DR

This paper introduces a novel method for compressing 3D mesh sequences with arbitrary topology by leveraging temporal correspondence and mesh deformation, achieving state-of-the-art compression performance for dynamic 3D data.

Contribution

It presents a new geometry and motion-based model for temporal correspondence, a mesh quality assessment, and an entropy-based encoding scheme for efficient compression of dynamic 3D meshes.

Findings

Achieves state-of-the-art compression ratios.

Handles meshes with arbitrary topology.

Demonstrates effectiveness through extensive experiments.

Abstract

With the advancement of computer vision, dynamic 3D reconstruction techniques have seen significant progress and found applications in various fields. However, these techniques generate large amounts of 3D data sequences, necessitating efficient storage and transmission methods. Existing 3D model compression methods primarily focus on static models and do not consider inter-frame information, limiting their ability to reduce data size. Temporal mesh compression, which has received less attention, often requires all input meshes to have the same topology, a condition rarely met in real-world applications. This research proposes a method to compress mesh sequences with arbitrary topology using temporal correspondence and mesh deformation. The method establishes temporal correspondence between consecutive frames, applies a deformation model to transform the mesh from one frame to subsequent frames, and replaces the original meshes with deformed ones if the quality meets a tolerance threshold. Extensive experiments demonstrate that this method can achieve state-of-the-art performance in terms of compression performance. The contributions of this paper include a geometry and motion-based model for establishing temporal correspondence between meshes, a mesh quality assessment for temporal mesh sequences, an entropy-based encoding and corner table-based method for compressing mesh sequences, and extensive experiments showing the effectiveness of the proposed method. All the code will be open-sourced at https://github.com/lszhuhaichao/ultron.