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Face and hands localization and tracking for sign language recognition
Author(s)
Soontranon, N.
Aramvith, S.
Chalidabhongse, T. H.
Date Issued
December 1, 2004
Type
Conference Paper
Abstract
In this paper, we develop the face and hand detection and tracking for sign language recognition system. We first perform preliminary evaluation on several color spaces to find the most suitable one using non-parametric model approach. Then, we propose to use the elliptical model on CbCr to lower the complexity of the detection algorithm and to better model the skin color. After the skin regions from the input video have been segmented, the interested facial features and hands are detected using luminance differences and skeleton features respectively. In the tracking stage, each blob determines search region and find MMSE (Minimum Mean Square Error) to match its own blob. The block matching method between previous and current frame is used. Experimental results show that our proposed system is able to detect and tracking face and hands of sign language video sequences.
Citation
IEEE International Symposium on Communications and Information Technologies Iscit 2004, 2, 1246-1251, 2004