Automatic 3D CBIR on kinematical human motion

Authors:
Chun-Hong Huang;Ching-Sheng Wang;Meng-Liang Yu
Affiliations:
Department of Computer Science and Information Engineering, Tamkang University,Taiwan, R.O.C.;Department of Computer and Information Science, Aletheia University, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, Tamkang University, Taiwan, R.O.C.
Venue:
CEA'07 Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and Applications
Year:
2007

Citing 6
Cited 1

Nonrigid motion analysis: articulated and elastic motion

Computer Vision and Image Understanding
Human Activity Recognition Using Multidimensional Indexing

IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity Retrieval of Human Motion As Multi-Stream Time Series Data

DANTE '99 Proceedings of the 1999 International Symposium on Database Applications in Non-Traditional Environments
Coupled hidden Markov models for complex action recognition

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Ribbon-Based Motion Analysis of Human Body Movements

ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Motion map: image-based retrieval and segmentation of motion data

SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation

A fuzzy qualitative framework for indoor rowing kinematics analysis

WSEAS Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Automatic retrieval of human body motion is one of the most challenging issues of video and virtual reality research. In this paper, we propose a human motion retrieval system, which allows users to retrieve 3D kinematical motions. The system includes two major components for motion analysis and comparison. The first is a recognition unit of motion types which is based on Skeleton Discrimination Tree. The second is a unit for synchronization and motion similarity comparison. The comparative approach is based on mutative dynamic programming that considers the degree of the included angles of the vectors belonging to individual feature tracks. With Motion Capture Camera and animations represented by VRML, it is possible to automatically summarize, analyze and adjust the 3D motions of a real person. Users may provide a 3D VRML human motion object and find the similar human motions via our system.