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Video feature descriptor combining motion and appearance cues with length-invariant characteristics

Abstract : Feature descriptor is one of the important subjects in video analysis problem. In this paper, we propose one video feature descriptor combining motion and appearance cues. The length-invariant characteristics of this proposed feature descriptor are clarified. Further, this feature descriptor is adopted to represent the video sequence for abnormal event detection problem, which is one challenging research field in the video surveillance. We proposed one abnormal event detection algorithm which consists of the feature descriptor and the nonlinear one-class classification method. Experiments on the benchmark dataset and comparisons with the state-of-the-art methods validate the advantages of our proposed feature descriptor.
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https://hal-utt.archives-ouvertes.fr/hal-03320779
Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Monday, August 16, 2021 - 1:56:51 PM
Last modification on : Wednesday, October 13, 2021 - 7:16:03 PM

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Tian Wang, Meina Qiao, Yang Chen, Jie Chen, Aichun Zhu, et al.. Video feature descriptor combining motion and appearance cues with length-invariant characteristics. Optik, Elsevier, 2018, 157, pp.1143-1154. ⟨10.1016/j.ijleo.2017.11.176⟩. ⟨hal-03320779⟩

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