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Spatio-Temporal Laplacian Pyramid Coding for Action Recognition
文献类型：期刊论文
| 作者 | Shao, Ling1,2; Zhen, Xiantong2; Tao, Dacheng3,4 ; Li, Xuelong5
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| 刊名 | ieee transactions on cybernetics
 |
| 出版日期 | 2014-06-01 |
| 卷号 | 44期号:6页码:817-827 |
| 关键词 | Action recognition computer vision max pooling spatio-temporal Laplacian pyramid |
| ISSN号 | 2168-2267 |
| 英文摘要 | we 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. |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | computer science, artificial intelligence ; computer science, cybernetics |
| 研究领域[WOS] | computer science |
| 关键词[WOS] | time interest points ; scene classification ; visual-attention ; features ; context ; representation ; appearance ; images ; model |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000337960000008 |
| 公开日期 | 2015-03-18 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/22362]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | 1.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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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