Abstract
Although the methods based on spatio-temporal interest points have shown promising results for human action recognition, they are not robust in complex scenes especially background clutter, camera motion, occlusions and illumination variations. In this paper, we propose a novel method to classify human actions in complex scenes. We suppress the false detection interest points by detecting salient regions. Furthermore, we encode the features according to their spatio-temporal relationship. Our method is verified on two challenging databases (UCF sports and YouTube), and the experimental results demonstrate that our method achieves better results than previous methods in human action recognition.
Keywords
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Zhang, Z., Liu, S., Liu, S., Han, L., Shao, Y., Zhou, W. (2015). Human Action Recognition using Salient Region Detection in Complex Scenes. In: Mu, J., Liang, Q., Wang, W., Zhang, B., Pi, Y. (eds) The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-08991-1_58
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DOI: https://doi.org/10.1007/978-3-319-08991-1_58
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08990-4
Online ISBN: 978-3-319-08991-1
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