Abstract

Real-time hand tracking is fundamental to human gesture recognition. However, due to the huge computation, previous studies are either off-line or limited to given poses. In order to satisfy the requirement of real-time hand tracking, in this paper we propose a real time hand tracking method using Kinect. Firstly we extract the hand region from the depth image output from Kinect. Then we achieve the hand parameters. During the procedure of hand region extraction, we propose a cascade structure with recursive connected component algorithm to improve the efficiency and reserve connection relationships in 3D space. To determine the fingertips, we use the former 3D connections and geodesic distance over hand skeleton pixels to guarantee the accuracy and robustness, with acceptable loss. Experimental results show that our proposed solution can significantly improve the quality of real-time hand tracking.

Keywords:
Robustness (evolution) Computer science Artificial intelligence Computer vision Pixel Computation Tracking (education) Cascade Geodesic Gesture Feature extraction Algorithm Mathematics Engineering

Metrics

22
Cited By
1.62
FWCI (Field Weighted Citation Impact)
12
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hand Gesture Recognition Systems
Physical Sciences →  Computer Science →  Human-Computer Interaction
Human Pose and Action Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Gaze Tracking and Assistive Technology
Physical Sciences →  Computer Science →  Human-Computer Interaction

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