Abstract
Precisely describing the action inside of a video is a challenging task because the content of the video includes various objects, with different local motion information at different speed in the video frames. In this paper, a new video feature is proposed based on the spatial information of the objects in a frame, along with the motion information between one against multiple consecutive frames. Motion information between pixels at the same position in the whole video are all combined for a new Spatial Multi-Scale Motion History Histogram (SMMHH) dynamic descriptor. The detailed algorithm of the SMMHH was given and it is tested in both human action recognition and touch gesture recognition applications based on the public video datasets. Experimental results demonstrate its excellent performance compared to other traditional methods.
A. Jan and Z. Zhao—Equal contribution.
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Jan, A., Zhao, Z., Chen, T., Meng, H., Lei, T. (2020). Spatial Multi-scale Motion History Histograms and Its Applications. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_79
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DOI: https://doi.org/10.1007/978-3-030-32591-6_79
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