Embedding Motion and Structure Features for Action Recognition
文献类型：期刊论文
| 作者 | Zhen, Xiantong1; Shao, Ling1; Tao, Dacheng2,3 ; Li, Xuelong4
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| 刊名 | ieee transactions on circuits and systems for video technology
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| 出版日期 | 2013-07-01 |
| 卷号 | 23期号:7页码:1182-1190 |
| 关键词 | Biologically inspired features discriminative locality alignment human action recognition |
| 英文摘要 | we propose a novel method to model human actions by explicitly coding motion and structure features that are separately extracted from video sequences. firstly, the motion template (one feature map) is applied to encode the motion information and image planes (five feature maps) are extracted from the volume of differences of frames to capture the structure information. the gaussian pyramid and center-surround operations are performed on each of the six obtained feature maps, decomposing each feature map into a set of subband maps. biologically inspired features are then extracted by successively applying gabor filtering and max pooling on each subband map. to make a compact representation, discriminative locality alignment is employed to embed the high-dimensional features into a low-dimensional manifold space. in contrast to sparse representations based on detected interest points, which suffer from the loss of structure information, the proposed model takes into account the motion and structure information simultaneously and integrates them in a unified framework; it therefore provides an informative and compact representation of human actions. the proposed method is evaluated on the kth, the multiview ixmas, and the challenging ucf sports datasets and outperforms state-of-the-art techniques on action recognition |
| WOS标题词 | science & technology ; technology |
| 类目[WOS] | engineering, electrical & electronic |
| 研究领域[WOS] | engineering |
| 关键词[WOS] | action representation ; scene classification ; object recognition ; localization ; context ; points ; images ; cortex ; scale |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000321276900009 |
| 公开日期 | 2015-06-30 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/24008]  |
| 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.Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 3JD, S Yorkshire, England 2.Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Ultimo, NSW 2007, Australia 3.Univ Technol Sydney, Fac Engn Informat Technol, Ultimo, NSW 2007, Australia 4.Chinese Acad Sci, Xian Inst Opt & Precisio Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhen, Xiantong,Shao, Ling,Tao, Dacheng,et al. Embedding Motion and Structure Features for Action Recognition[J]. ieee transactions on circuits and systems for video technology,2013,23(7):1182-1190. |
| APA | Zhen, Xiantong,Shao, Ling,Tao, Dacheng,&Li, Xuelong.(2013).Embedding Motion and Structure Features for Action Recognition.ieee transactions on circuits and systems for video technology,23(7),1182-1190. |
| MLA | Zhen, Xiantong,et al."Embedding Motion and Structure Features for Action Recognition".ieee transactions on circuits and systems for video technology 23.7(2013):1182-1190. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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