Work

A Method for Generating Geometric Image Sequences for Non-Isomorphic 3D-Mesh Sequence Compression

Year: 2023

Type: article

Abstract: As virtual reality and 3D-modeling technology continue to advance, the amount of digital geometric media data is growing at an explosive rate. For example, 3D meshes, an important type of digital geometric media, can precisely record geometric information on a model’s surface. However, as the complexity and precision of 3D meshes increase, it becomes more challenging to store and transmit them. The traditional method of compressing non-isomorphic 3D-mesh sequences through frame-by-frame compression is inefficient and destroys the inter-frame correlations of the sequences. To tackle these issues, this study investigates the generation of time-dependent geometric image sequences for compressing non-isomorphic 3D-mesh sequences. Two methods are proposed for generating such sequences: one through image registration and the other through parametrization-geometry cooperative registration. Based on the experimental compression results of the video-coding algorithms, it was observed that the proposed geometric image-sequence-generation method offers superior objective and subjective qualities, as compared to the traditional method.

Source: Electronics

DOI: 10.3390/electronics12163473

Authors: Yuan Gao, Zhiqiang Wang, Jin Wen

Institution: Beijing Electronic Science and Technology Institute

Language: English

Topic: Video Coding and Compression Technologies

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,224

Funder: Fundamental Research Funds for the Central Universities