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Dynamic gesture recognition using PCA with multi-scale theory and HMM

Wu, Hai and Sutherland, Alistair (2001) Dynamic gesture recognition using PCA with multi-scale theory and HMM. In: SPIE International Symposium on Multispectral Image Processing and Pattern Recognition, Vol. 4550, 22-24 October 2001, Wuhan, China.

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Abstract

In this paper, a dynamic gesture recognition system is presented which requires no special hardware other than a Webcam. The system is based on a novel method combining Principal Component Analysis (PCA) with hierarchical multi-scale theory and Discrete Hidden Markov Models (DHMM). We use a hierarchical decision tree based on multiscale theory. Firstly we convolve all members of the training data with a Gaussian kernel, which blurs differences between images and reduces their separation in feature space. This reduces the number of eigenvectors needed to describe the data. A principal component space is computed from the convolved data. We divide the data in this space into two clusters using the k-means algorithm. Then the level of blurring is reduced and PCA is applied to each of the clusters separately. A new principal component space is formed from each cluster. Each of these spaces is then divided into two and the process is repeated. We thus produce a binary tree of principal component spaces where each level of the tree represents a different degree of blurring. The search time is then proportional to the depth of the tree, which makes it possible to search hundreds of gestures in real time. The output of the decision tree is then input into DHMM to recognize temporal information.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:PCA; Multi-scale theory; Decision tree; DHMM;
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Optical Society of America
Official URL:http://dx.doi.org/10.1117/12.441451
Copyright Information:Copyright 2001 Society of Photo-Optical Instrumentation Engineers. This paper was published in Proceedings of SPIE - Volume 4550: Image Extraction, Segmentation, and Recognition and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
ID Code:349
Deposited On:14 Mar 2008 by DORAS Administrator. Last Modified 04 Feb 2009 10:51

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