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Pattern Recognition Letters
Volume 21, Issue 1, January 2000, Pages 69-82
 
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doi:10.1016/S0167-8655(99)00134-8    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2000 Elsevier Science B.V. All rights reserved.

User-independent online gesture recognition by relative motion extraction

Bisser Raytchev Corresponding Author Contact Information, E-mail The Corresponding Author, a, b, Osamu Hasegawa E-mail The Corresponding Author, b and Nobuyuki Otsu E-mail The Corresponding Author, a, b

a Department of Informatics and Electronics, Tsukuba University, Tsukuba, Japan Adaptive Vision Lab, Machine Understanding Division, ETL, 1-1-4 Umezono, Tsukuba 305 8568, Japan1

Received 29 March 1999; 
Revised 21 September 1999. 
Available online 23 December 1999.

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Abstract

We propose a new method for user-independent gesture recognition from time-varying images. The method uses relative motion-dependent feature extraction, together with discriminant analysis and dynamically updated buffer structures for providing online learning/recognition abilities. Efficient and robust extraction/representation of information about motion is achieved. Being computationally inexpensive the method allows real-time performance.

Author Keywords: Author Keywords: User-independent online gesture recognition; Human–computer interface (HCI); Relative motion extraction; Discriminant analysis; Machine learning

Article Outline

1. Introduction
2. Description of the method
2.1. Primitive feature extraction
2.2. Projection to discriminant feature space
2.3. Dynamic buffer structures (DBS)
3. Experimental results
3.1. Multimodal database of gestures with speech (MMDB)
3.2. “Real-world” data
4. Conclusion and further work
Acknowledgements
References








 
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