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2008
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Automatic generation of HMM topology for sign language recognition

11 years 2 months ago
Automatic generation of HMM topology for sign language recognition
Sign language is used for communicating to people with hearing difficulties. Recogntion of a sign language image sequence is challenging because of the variety of hand shapes and hand motions. We propose a method to automatically construct a transitional structure(topology) of a Hidden Markov Model(HMM) for recognizing sign language words. Unlike conventional HMM, the constructed topology has branches and junctions in order to represent a flexible structure. The proposed method consists of segmentation of a motion, and construction of the topology from segments. The topology is constructed from an initial topology by modifying it. With experiments, we show the effectiveness of the proposed method.
Tadashi Matsuo, Yoshiaki Shirai, Nobutaka Shimada
Added 05 Nov 2009
Updated 06 Nov 2009
Type Conference
Year 2008
Where ICPR
Authors Tadashi Matsuo, Yoshiaki Shirai, Nobutaka Shimada
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