A Robust Hand Tracking Approach Based on Modified Tracking-Learning-Detection Algorithm

Hand tracking is an essential step for dynamic gesture recognition which catches a lot of attention in the field of gesture interaction. In this paper, we present a robust hand tracking approach for unconstrained videos based on modified Tracking-Learning-Detection (TLD) algorithm, named BP-TLD. By introducing a skin color feature to the model, we make the algorithm more suitable for hand tracking. The experimental results show that BP-TLD has a better performance compared with other tracking algorithms such as TLD, MSEPF and Handvu. It indicates that our approach can meet the requirements of robustness and real-time better for the frontal-view vision-based human computer interactions.