Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Supervised Learning for Visual Tracking and Recognition of Human Hand
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Continuous hand gesture segmentation and co-articulation detection
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Multimedia Tools and Applications
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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.