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Dense Trajectories and Motion Boundary Descriptors for Action Recognition
文献类型:期刊论文
作者 | Wang, Heng1; Klaeser, Alexander2; Schmid, Cordelia2; Liu, Cheng-Lin1![]() |
刊名 | INTERNATIONAL JOURNAL OF COMPUTER VISION
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出版日期 | 2013-05-01 |
卷号 | 103期号:1页码:60-79 |
关键词 | Action recognition Dense trajectories Motion boundary histograms |
英文摘要 | This paper introduces a video representation based on dense trajectories and motion boundary descriptors. Trajectories capture the local motion information of the video. A dense representation guarantees a good coverage of foreground motion as well as of the surrounding context. A state-of-the-art optical flow algorithm enables a robust and efficient extraction of dense trajectories. As descriptors we extract features aligned with the trajectories to characterize shape (point coordinates), appearance (histograms of oriented gradients) and motion (histograms of optical flow). Additionally, we introduce a descriptor based on motion boundary histograms (MBH) which rely on differential optical flow. The MBH descriptor shows to consistently outperform other state-of-the-art descriptors, in particular on real-world videos that contain a significant amount of camera motion. We evaluate our video representation in the context of action classification on nine datasets, namely KTH, YouTube, Hollywood2, UCF sports, IXMAS, UIUC, Olympic Sports, UCF50 and HMDB51. On all datasets our approach outperforms current state-of-the-art results. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Artificial Intelligence |
研究领域[WOS] | Computer Science |
关键词[WOS] | OBJECT TRAJECTORIES ; FEATURES ; VIDEO ; CLASSIFICATION ; TEXTURE ; SCALE |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000318413500003 |
源URL | [http://ir.ia.ac.cn/handle/173211/3075] ![]() |
专题 | 自动化研究所_模式识别国家重点实验室_模式分析与学习团队 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 2.INRIA Grenoble Rhone Alpes, LEAR Team, F-38330 Montbonnot St Martin, France |
推荐引用方式 GB/T 7714 | Wang, Heng,Klaeser, Alexander,Schmid, Cordelia,et al. Dense Trajectories and Motion Boundary Descriptors for Action Recognition[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2013,103(1):60-79. |
APA | Wang, Heng,Klaeser, Alexander,Schmid, Cordelia,&Liu, Cheng-Lin.(2013).Dense Trajectories and Motion Boundary Descriptors for Action Recognition.INTERNATIONAL JOURNAL OF COMPUTER VISION,103(1),60-79. |
MLA | Wang, Heng,et al."Dense Trajectories and Motion Boundary Descriptors for Action Recognition".INTERNATIONAL JOURNAL OF COMPUTER VISION 103.1(2013):60-79. |
入库方式: OAI收割
来源:自动化研究所
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