Abstract
This paper presents a novel approach to reliably tracking multiple fingertips simultaneously using a single optical camera. The proposed technique uses the skin color model to extract the hand region and identifies fingertips via curvature detection. It can remove different types of interfering points through the cross product of vectors and the distance transform. Finally, an improved Kalman filter is employed to predict the locations of fingertips in the current image frame and this information is exploited to associate fingertips with those in the previous image frame to build a complete trajectory. Experimental results show that this method can achieve robust continuous fingertip tracking in a real-time manner.
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Wang, C., Yuan, B. (2014). Robust Fingertip Tracking with Improved Kalman Filter. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_67
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DOI: https://doi.org/10.1007/978-3-319-09333-8_67
Publisher Name: Springer, Cham
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