Dynamic Hand Gesture Recognition Based On Randomized Self-Organizing Map Algorithm
Authors: Tarek El. Tobely, Yuichiro Yoshiki, Ryuichi Tsuda, Naoyuki Tsuruta, and Makoto Amamiya .
Source: Lecture Notes in Artificial Intelligence Vol. 1968, 2000, 252 - 263.
Abstract. Gesture recognition is an appealing tool for natural interface with computers especially for physically impaired persons. In this paper, it is proposed to use Self-Organized Map (SOM) to recognize the posture images of hand gestures. Since the competition algorithm of SOM allows alleviating many diãculties associated with gesture recognition. However, it is required to reduce the recognition time of one image in SOM network to the range of normal video camera rates, this permits the network to accept dynamic input images and to perform on-line recognition for hand gestures. To achieve this, the Randomized Self-Organizing Map algorithm (RSOM) is proposed as a new recognition algorithm for SOM. With RSOM algorithm, the recognition time of one image reduced to 12.4 % of the normal SOM competition algorithm with 100 % accuracy and allowed the network to recognize images within the range of normal video rates. The experimental results to recognize six dynamic hand gestures using RSOM algorithm is presented.
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