Abstract
In this paper we apply the Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) descriptor to the field of human action recognition. A video sequence is described as a collection of spatial-temporal words after the detection of space-time interest points and the description of the area around them. Our contribution has been in the description part, showing LBP-TOP to be a promising descriptor for human action classification purposes. We have also developed several extensions to the descriptor to enhance its performance in human action recognition, showing the method to be computationally efficient.
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Mattivi, R., Shao, L. (2009). Human Action Recognition Using LBP-TOP as Sparse Spatio-Temporal Feature Descriptor. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_90
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DOI: https://doi.org/10.1007/978-3-642-03767-2_90
Publisher Name: Springer, Berlin, Heidelberg
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