A Fuzzy Clustering Algorithm for Virtual Character Animation Representation

The use of realistic humanoid animations generated through motion capture (MoCap) technology is widespread across various 3-D applications and industries. However, the existing compression techniques for such representation often do not consider the implicit coherence within the anatomical structure...

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Bibliographic Details
Published in:IEEE transactions on multimedia 2011-02, Vol.13 (1), p.40-49
Main Authors: CHEW, Boon-Seng, CHAU, Lap-Pui, YAP, Kim-Hui
Format: Article
Language:English
Subjects:
Animation
Applied sciences
Artificial intelligence
Clustering algorithms
Coherence
Compression
Computer science
control theory
systems
Computer systems and distributed systems. User interface
Data processing. List processing. Character string processing
Exact sciences and technology
fuzzy c-mean clustering and realism
Image coding
Joints
Memory organisation. Data processing
Pattern recognition. Digital image processing. Computational geometry
Software
Three dimensional displays
Transform coding
virtual character animation
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Summary:The use of realistic humanoid animations generated through motion capture (MoCap) technology is widespread across various 3-D applications and industries. However, the existing compression techniques for such representation often do not consider the implicit coherence within the anatomical structure of a human skeletal model and lacks portability for transmission consideration. In this paper, a novel concept virtual character animation image (VCAI) is proposed. Built upon a fuzzy clustering algorithm, the data similarity within the anatomy structure of a virtual character (VC) model is jointly considered with the temporal coherence within the motion data to achieve efficient data compression. Since the VCA is mapped as an image, the use of image processing tool is possible for efficient compression and delivery of such content across dynamic network. A modified motion filter (MMF) is proposed to minimize the visual discontinuity in VCA's motion due to the quantization and transmission error. The MMF helps to remove high frequency noise components and smoothen the motion signal providing perceptually improved VCA with lessened distortion. Simulation results show that the proposed algorithm is competitive in compression efficiency and decoded VCA quality against the state-of-the-art VCA compression methods, making it suitable for providing quality VCA animation to low-powered mobile devices.
ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2010.2082512