Abstract
Hand tracking in complicate scenarios is a crucial step to any hand gesture recognition systems. In this paper, we present a novel hand tracking algorithm with adaptive hand appearance modeling. In the algorithm, the hand image is first transformed to the grids of Histograms of Oriented Gradients. And then an incremental Principle Component Analysis is implemented. We name this operator an incremental PCA-HOG (IPHOG) descriptor. The exploitation of this descriptor helps the tracker dealing with vast changing of hand appearances as well as clutter background. Moreover, Particle filter method with certain improvements is also introduced to establish a tracking framework. The experimental results are conducted on an indoor scene with clutter and dynamic background. And the results are also compared with some traditional tracking algorithms to show its strong robustness and higher tracking accuracy.
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Yang, H., Song, Z., Chen, R. (2010). An Incremental PCA-HOG Descriptor for Robust Visual Hand Tracking. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_67
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DOI: https://doi.org/10.1007/978-3-642-17274-8_67
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