A study on the gesture recognition based on the particle filter

Authors:
Hyung Kwan Kim;Yang Weon Lee;Chil Woo Lee
Affiliations:
Department of Computer engineering, Chonnam University, Gwangju, South Korea;Department of Information and Communication Engineering, Honam University, Gwangju, South Korea;Department of Computer Engineering, Chonnam University, Gwangju, South Korea
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Year:
2007

Citing 4
Cited 0

CONDENSATION—Conditional Density Propagation forVisual Tracking

International Journal of Computer Vision
A Probabilistic Framework for Matching Temporal Trajectories: CONDENSATION-Based Recognition of Gestures and Expressions

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Abstract

The recognition of human gestures in image sequences is an important and challenging problemthat enables a host of human-computer interaction applications. This paper describes a gesture recognition algorithm based on the particle filters, namely CONDENSATION. The particle filter is more efficient than any other tracking algorithm because the tracking mechanism follows Bayesian estimation rule of conditional probability propagation. We used two models for the evaluation of particle filter and apply the MATLAB for the preprocessing of the image sequence. But we implement the particle filter using the C++ to get the high speed processing. In the experimental results, it is demonstrated that the proposed algorithm prove to be robust in the cluttered environment.