Compressed Dynamic Mesh Sequence for Progressive Streaming

Yang, Bailin; Jiang, Zhaoyi; Shangguan, Jiantao; Li, Frederick W.B.; Song, Chao; Guo, Yibo; Xu, Mingliang

Abstract

Dynamic mesh sequence (DMS) is a simple and accurate representation for precisely recording a 3D animation sequence. Despite its simplicity, this representation is typically large in data size, making storage and transmission expensive. This paper presents a novel framework that allows effective DMS compression and progressive streaming by eliminating spatial and temporal redundancy. To explore temporal redundancy, we propose a temporal frame‐clustering algorithm to organize DMS frames by their motion trajectory changes, eliminating intracluster redundancy by principal component analysis dimensionality reduction. To eliminate spatial redundancy, we propose an algorithm to transform the coordinates of mesh vertex trajectory into a decorrelated trajectory space, generating a new spatially nonredundant trajectory representation. We finally apply a spectral graph wavelet transform with color set partitioning embedded block encoding to turn the resultant DMS into a multiresolution representation to support progressive streaming. Experiment results show that our method outperforms several existing methods in terms of storage requirement and reconstruction quality.

Citation

Yang, B., Jiang, Z., Shangguan, J., Li, F. W., Song, C., Guo, Y., & Xu, M. (2019). Compressed Dynamic Mesh Sequence for Progressive Streaming. Computer Animation and Virtual Worlds, 30(6), Article e1847. https://doi.org/10.1002/cav.1847

• Journal Article Type: Article
• Acceptance Date: May 25, 2018
• Online Publication Date: Jul 30, 2018
• Publication Date: Nov 30, 2019
• Deposit Date: Jul 7, 2018
• Publicly Available Date: Jul 30, 2019
• Journal: Computer Animation and Virtual Worlds
• Print ISSN: 1546-4261
• Electronic ISSN: 1546-427X
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 6
• Article Number: e1847
• DOI: https://doi.org/10.1002/cav.1847
• Public URL: https://durham-repository.worktribe.com/output/1354861