Coding of motion capture data via temporal-domain sampling and spatial-domain vector quantization techniques

Authors:
May-chen Kuo;Pei-Ying Chiang;C.-C. Jay Kuo
Affiliations:
Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA;Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA;Ming-Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA
Venue:
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Year:
2010

Citing 10
Cited 0

Motion interpolation by optimal control

SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Motion graphs

Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Dynamic response for motion capture animation

ACM SIGGRAPH 2005 Papers
A data-driven approach to quantifying natural human motion

ACM SIGGRAPH 2005 Papers
Compression of motion capture databases

ACM SIGGRAPH 2006 Papers
Human Motion Capture Data Compression by Model-Based Indexing: A Power Aware Approach

IEEE Transactions on Visualization and Computer Graphics
Physics-based motion retiming

Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Optimized MPEG-4 animation encoder for motion capture data

Proceedings of the twelfth international conference on 3D web technology
Adapting wavelet compression to human motion capture clips

GI '07 Proceedings of Graphics Interface 2007
Active learning for real-time motion controllers

ACM SIGGRAPH 2007 papers

Quantified Score

Hi-index	0.01

Visualization

Abstract

The motion capture (mocap) data has been widely used in motion synthesis applications. In this research, we explore the characteristics of mocap data to develop a new generic and fully-automated compression framework that allows a flexible rate-quality trade-off. The coding framework consists of three modules: 1) temporal sampling, 2) vector quantization in selected I-frames and 3) interpolation and residual coding. The proposed framework gives a higher compression ratio at lower complexity than the state-of-the-art mocap data coding algorithm. It is shown by experimental results that the proposed scheme can achieve 20:1 compression ratio while providing good quality motion.