Orientation Histograms for Hand Gesture Recognition
نویسندگان
چکیده
We present a method to recognize hand gestures, based on a pattern recognition technique developed by McConnell [16] employing histograms of local orientation. We use the orientation histogram as a feature vector for gesture classification and interpolation. For moving or d̈ynamic gestures,̈ the histogram of the spatio-temporal gradients of image intensity form the analogous feature vector and may be useful for dynamic gesture recognition. IEEE Intl. Wkshp. on Automatic Face and Gesture Recognition, Zurich, June, 1995 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 1994 201 Broadway, Cambridge, Massachusetts 02139
منابع مشابه
MITSUBISHI ELECTRIC RESEARCH LABORATORIES CAMBRIDGE RESEARCH CENTER Orientation Histograms for Hand Gesture Recognition
We present a method to recognize hand gestures, based on a pattern recognition technique developed by McConnell [16] employing histograms of local orientation. We use the orientation histogram as a feature vector for gesture class cation and interpolation. This method is simple and fast to compute, and o ers some robustness to scene illumination changes. We have implemented a real-time version,...
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