Real-time wrist localization in color images based on corner analysis

Hand detection and gestures recognition have become very popular in recent human-computer interaction systems. Although several methods of hand detection have been proposed in the literature, they exist few methods that use the wrist as a factor of detection, others impose constraints on the length of the sleeves and on the orientation of the hand. In this work, we present a new two-stage algorithm of wrist localization designed for hand detection and gestures recognition systems. The first stage of the algorithm consists in separating the skin region containing the hand from the background, and in the second stage, the wrist is localized from the resulted skin mask. The main contribution of the proposed method is based on the analysis of corners along the contour of the skin masks to localize the wrist emplacement. Based on an evaluation on 437 color images with their ground-truth and three sets of skin masks, we compared our method with other efficient methods of literature and the results obtained were very satisfactory.