Abstract:
:This paper presents a fast and simple method for human action recognition. The proposed technique relies on detecting interest points using SIFT (scale invariant feature transform) from each frame of the video. A fine-tuning step is used here to limit the number of interesting points according to the amount of details. Then the popular approach Bag of Video Words is applied with a new normalization technique. This normalization technique remarkably improves the results. Finally a multi class linear Support Vector Machine (SVM) is utilized for classification. Experiments were conducted on the KTH and Weizmann datasets. The results demonstrate that our approach outperforms most existing methods, achieving accuracy of 97.89% for KTH and 96.66% for Weizmann.
journal_name
J Adv Resjournal_title
Journal of advanced researchauthors
Moussa MM,Hamayed E,Fayek MB,El Nemr HAdoi
10.1016/j.jare.2013.11.007subject
Has Abstractpub_date
2015-03-01 00:00:00pages
163-9issue
2eissn
2090-1232issn
2090-1224pii
S2090-1232(13)00143-4journal_volume
6pub_type
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journal_title:Journal of advanced research
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pub_type: 杂志文章
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