Gesture recognition methods based on intensity or color images often suffer from low efficiency and lack of robustness. In this paper, we employ a new laser-based camera that produces reliable low-resolution depth images at video rates. By decomposing and recognizing hand poses as finger states (finger poses and finger inter-relations), we achieve robust hand pose recognition in real-time (30 frames/second).
Citation:
Zhenyao Mo, Ulrich Neumann, "Real-time Hand Pose Recognition Using Low-Resolution Depth Images," cvpr, vol. 2, pp.1499-1505, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06), 2006