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Hand gesture recognition from visual images finds applications in areas like human computer interaction, machine vision, virtual reality and so on. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we present a model-based method for tracking hand motion in a complex scene, thereby estimating the hand motion trajectory. In our proposed technique, we first segment the frames into video object planes (VOPs) with the hand as the video object. This is followed by hand tracking using Hausdorff tracker. In the next step, the centroids of all VOPs are calculated using moments as well as motion information. Finally, the hand trajectory is estimated by joining the VOP centroids. In our experiment, the proposed trajectory estimation algorithm gives about 99% accuracy in finding the actual trajectory.

Estimation of 2D Motion Trajectories from Video Object Planes and Its Application in Hand Gesture Recognition