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The sign language recognition is the most popular research area involving computer vision, pattern recognition and image processing. It enhances communication capabilities of the mute person. In this paper, we present an object based key frame selection., Hausdorff distance, Forward Algorithm and Euclidean distance are used for shape similarity for hand gesture recognition. We proposed use to the...
We investigate the issue of sign language automatic phonetic subunit modeling, that is completely data driven and without any prior phonetic information. A first step of visual processing leads to simple and effective region-based visual features. Prior to the sub-unit modeling we propose to employ a pronunciation clustering step with respect to each sign. Afterwards, for each sign and pronunciation...
This work presents a piecewise linear approximation to non-linear Point Distribution Models for modelling the human hand. The work utilises the natural segmentation of shape space, inherent to the technique, to apply temporal constraints, which can be used with CONDENSATION to support multiple hypotheses and discontinuous jumps within shape space. This paper presents a novel method by which the one-state...
Principal component analysis (PCA) and multiple discriminant analysis (MDA) have long been used for appearance-based hand posture recognition. In this paper, we propose a novel PCA/MDA scheme for hand posture recognition. The scheme is represented by two layers of nodes (classes). The first layer of nodes acts as a crude classification using PCA, and each input pattern is given a likelihood of being...
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