Abstract
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.
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Shi, H., Lin, Z., Tang, W., Liao, B., Wang, J., Zheng, L. (2014). A Robust Hand Tracking Approach Based on Modified Tracking-Learning-Detection Algorithm. In: Park, J., Chen, SC., Gil, JM., Yen, N. (eds) Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54900-7_2
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DOI: https://doi.org/10.1007/978-3-642-54900-7_2
Publisher Name: Springer, Berlin, Heidelberg
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