A spatial hierarchical compression method for 3D streaming animation
VRML '00 Proceedings of the fifth symposium on Virtual reality modeling language (Web3D-VRML)
Advanced real-time collaboration over the internet
VRST '00 Proceedings of the ACM symposium on Virtual reality software and technology
Adaptation of Facial and Body Animation for MPEG-based Architectures
CW '03 Proceedings of the 2003 International Conference on Cyberworlds
Agents That Talk And Hit Back: Animated Agents in Augmented Reality
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
A Distributed Multiuser Virtual Space System
IEEE Computer Graphics and Applications
Human Motion Capture Data Compression by Model-Based Indexing: A Power Aware Approach
IEEE Transactions on Visualization and Computer Graphics
Optimized MPEG-4 animation encoder for motion capture data
Proceedings of the twelfth international conference on 3D web technology
3D game content distributed adaptation in heterogeneous environments
EURASIP Journal on Advances in Signal Processing
An Efficient Wavelet-Based Framework for Articulated Human Motion Compression
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
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Animation of Virtual Humans (avatars) is done typically using motion data files that are stored on a client or streaming motion data from a server. Several modern applications require avatar animation in mobile networked virtual environments comprising of power constrained clients such as PDAs, Pocket-PCs and notebook PCs operating in battery mode. These applications call for efficient compression of the motion animation data in order to conserve network bandwidth, and save power at the client side during data reception and motion data reconstruction from the compressed file. In this paper, we have proposed and implemented a novel file format, termed the Quantized Motion Data (QMD) format, which enables significant, though lossy, compression of the motion data. The motion distortion resulting from the reconstructed motion from the QMD file is minimized by intelligent use of the hierarchical structure of the skeletal avatar model. The compression gained by using the QMD files for the motion data is more than twice achieved via standard MPEG-4 compression using a pipeline comprising of quantization, predictive encoding and arithmetic coding. In addition, considerably fewer CPU cycles are needed to reconstruct the motion data from the QMD files compared to motion data compressed using the MPEG-4 standard.