Free hand sketch understanding using SVMs-chain modeling for spatial and temporal patterns

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Free hand sketch understanding using SVMs-chain modeling for spatial and temporal patterns

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ACM/SIGEVO Summit on Genetic and Evolutionary Computation archive
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation table of contents

Shanghai, China

POSTER SESSION: Poster sessions table of contents

Pages 1029-1032

Year of Publication: 2009

ISBN:978-1-60558-326-6

Authors

Kun Yang	Department of Mathematics, Shanghai Jiao Tong University, Shanghai, China
Jingwei Ye	School of Microelectronics, Shanghai Jiao Tong University, Shanghai, China
Zhijun Li	Department of Automation, Shanghai Jiao Tong University, Shanghai, China
Yu Qiao	Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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ABSTRACT

The growing popularity of tablet PCs and intelligent pen-centric computing have increased the importance of freehand sketch recognition algorithms. This paper shall investigate the use of information fusion technique with Support Vector Machines (SVMs) chain for modeling and understanding the spatial and temporal information of sketch sequences. The approach for sketch recognition lies in the proposed dynamic and probabilistic framework based on combining SVMs-chain by the spatial and geometric features for systematically modeling the dynamic and stochastic behaviors of sketch.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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