Self-directed-learning for sign language recognition
ISCGAV'09 Proceedings of the 9th WSEAS international conference on Signal processing, computational geometry and artificial vision
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In this paper, we present an algorithm for evaluating the similarity of pairs of signs used in sign language. The proposed algorithm is based on the visual similarity on the sign and compares sequences of static positions of the signing person. The algorithm does not rely on any particular way of obtaining necessary geometric form of signs. The usability of the proposed algorithm has already been tested in its pilot implementation in a dictionary between Czech and Czech Sign Language. Geometric data available for a 3D animated model was used to enhance the dictionary with the possibility of searching for signs in dictionary according to partial information obtained from the user as well as retrieval of visually similar signs for a currently selected one.