LF-EME:Local features with elastic manifold embedding for human
文献类型：期刊论文
| 作者 | Xiaoyu Deng; Xiao Liu; Mingli Song; Jun Cheng; Jiajun Bu; Chun Chen |
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2013 |
| 英文摘要 | Human action recognition has been an active topic in computer vision. Currently, most of the approaches to this problem can be categorized into two classes. One is based on local features, and the other is based on global features. Meanwhile, manifold learning has become successful in many problems in computer vision, but because of the high variability of human body, the application of manifold learning to human action recognition is limited. We propose a framework based on Elastic Manifold Embedding (EME), a new sparse manifold learning algorithm, together with local interest point features to handle human action recognition. The result of the new framework is very promising in comparison with state-of-the-art methods. |
| 收录类别 | SCI |
| 原文出处 | http://www.sciencedirect.com/science/article/pii/S0925231212004833 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4440]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | NEUROCOMPUTING |
| 推荐引用方式 GB/T 7714 | Xiaoyu Deng,Xiao Liu,Mingli Song,et al. LF-EME:Local features with elastic manifold embedding for human[J]. NEUROCOMPUTING,2013. |
| APA | Xiaoyu Deng,Xiao Liu,Mingli Song,Jun Cheng,Jiajun Bu,&Chun Chen.(2013).LF-EME:Local features with elastic manifold embedding for human.NEUROCOMPUTING. |
| MLA | Xiaoyu Deng,et al."LF-EME:Local features with elastic manifold embedding for human".NEUROCOMPUTING (2013). |
入库方式： OAI收割
来源：深圳先进技术研究院
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