| Embedding Motion and Structure Features for Action Recognition | |
Zhen, Xiantong1; Shao, Ling1; Tao, Dacheng2,3 ; Li, Xuelong4
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| 2013-07-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
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| 卷号 | 23期号:7页码:1182-1190 |
| 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 |
| 文章类型 | Article |
| 关键词 | Biologically Inspired Features Discriminative Locality Alignment Human Action Recognition |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TCSVT.2013.2240916 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | ACTION REPRESENTATION ; SCENE CLASSIFICATION ; OBJECT RECOGNITION ; LOCALIZATION ; CONTEXT ; POINTS ; IMAGES ; CORTEX ; SCALE |
| 语种 | 英语 |
| WOS研究方向 | Engineering |
| WOS类目 | Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000321276900009 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/24008 |
| 专题 | 光谱成像技术研究室 |
| 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. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Embedding Motion and（1804KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
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