标题:Learning action patterns in difference images for efficient action recognition
作者:Lu, Guoliang; Kudo, Mineichi
作者机构:[Lu, Guoliang; Kudo, Mineichi] Hokkaido Univ, Grad Sch Informat Sci & Technol, Sapporo, Hokkaido 0600814, Japan.; [Lu, Guoliang] Shandong Univ, Sch 更多
通讯作者:Lu, G
通讯作者地址:[Lu, GL]Hokkaido Univ, Grad Sch Informat Sci & Technol, Sapporo, Hokkaido 0600814, Japan.
来源:NEUROCOMPUTING
出版年:2014
卷:123
页码:328-336
DOI:10.1016/j.neucom.2013.06.042
关键词:Action patterns; Efficient action recognition; Temporal; self-similarities; Bag-of-words
摘要:A new framework is presented for single-person oriented action recognition. This framework does not require detection/location of bounding boxes of human body nor motion estimation in each frame. The novel descriptor/pattern for action representation is learned with local temporal self-similarities (LTSSs) derived directly from difference images. The bag-of-words framework is then employed for action classification taking advantages of these descriptors. We investigated the effectiveness of the framework on two public human action datasets: the Weizmann dataset and the KTH dataset In the Weizmann dataset, the proposed framework achieves a performance of 95.6% in the recognition rate and that of 91.1% in the KTH dataset, both of which are competitive with those of state-of-the-art approaches, but it has a high potential to achieve a faster execution performance. (C) 2013 Elsevier B.V. All rights reserved.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:6
Scopus被引频次:11
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885762171&doi=10.1016%2fj.neucom.2013.06.042&partnerID=40&md5=decd76b3c3d5294e2b710cf0ba2eb2f6
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