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Spatio-Temporal Laplacian Pyramid Coding for Action Recognition
Shao, Ling1,2; Zhen, Xiantong2; Tao, Dacheng3,4; Li, Xuelong5
Department光学影像学习与分析中心
2014-06-01
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
ISSN2168-2267
Volume44Issue:6Pages:817-827
AbstractWe present a novel descriptor, called spatio-temporal Laplacian pyramid coding (STLPC), for holistic representation of human actions. In contrast to sparse representations based on detected local interest points, STLPC regards a video sequence as a whole with spatio-temporal features directly extracted from it, which prevents the loss of information in sparse representations. Through decomposing each sequence into a set of band-pass-filtered components, the proposed pyramid model localizes features residing at different scales, and therefore is able to effectively encode the motion information of actions. To make features further invariant and resistant to distortions as well as noise, a bank of 3-D Gabor filters is applied to each level of the Laplacian pyramid, followed by max pooling within filter bands and over spatio-temporal neighborhoods. Since the convolving and pooling are performed spatio-temporally, the coding model can capture structural and motion information simultaneously and provide an informative representation of actions. The proposed method achieves superb recognition rates on the KTH, the multiview IXMAS, the challenging UCF Sports, and the newly released HMDB51 datasets. It outperforms state of the art methods showing its great potential on action recognition.
SubtypeArticle
KeywordAction Recognition Computer Vision Max Pooling Spatio-temporal Laplacian Pyramid
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TCYB.2013.2273174
Indexed BySCI ; EI
WOS KeywordTIME INTEREST POINTS ; SCENE CLASSIFICATION ; VISUAL-ATTENTION ; FEATURES ; CONTEXT ; REPRESENTATION ; APPEARANCE ; IMAGES ; MODEL
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000337960000008
Citation statistics
Cited Times:141[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/22362
Collection光学影像学习与分析中心
Affiliation1.Nanjing Univ Informat Sci & Technol, Coll Elect & Informat Engn, Nanjing 210044, Jiangsu, Peoples R China
2.Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 3JD, S Yorkshire, England
3.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia
4.Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia
5.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning, Xian 710119, Peoples R China
Recommended Citation
GB/T 7714
Shao, Ling,Zhen, Xiantong,Tao, Dacheng,et al. Spatio-Temporal Laplacian Pyramid Coding for Action Recognition[J]. IEEE TRANSACTIONS ON CYBERNETICS,2014,44(6):817-827.
APA Shao, Ling,Zhen, Xiantong,Tao, Dacheng,&Li, Xuelong.(2014).Spatio-Temporal Laplacian Pyramid Coding for Action Recognition.IEEE TRANSACTIONS ON CYBERNETICS,44(6),817-827.
MLA Shao, Ling,et al."Spatio-Temporal Laplacian Pyramid Coding for Action Recognition".IEEE TRANSACTIONS ON CYBERNETICS 44.6(2014):817-827.
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