CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
Mid-level features and spatio-temporal context for activity recognition
Yuan, Fei1,2; Xia, Gui-Song3; Sahbi, Hichem2; Prinet, Veronique1
Source PublicationPATTERN RECOGNITION
2012-12-01
Volume45Issue:12Pages:4182-4191
SubtypeArticle
AbstractLocal spatio-temporal features have been shown to be effective and robust in order to represent simple actions. However, for high level human activities with long-range motion or multiple interactive body parts and persons, the limitation of low-level features blows up because of their localness. This paper addresses the problem by suggesting a framework that computes mid-level features and takes into account their contextual information.
KeywordActivity Recognition Mid-level Features Activity Components Spatio-temporal Context Kernels
WOS HeadingsScience & Technology ; Technology
WOS KeywordIMAGE SEGMENTATION ; SPACE
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000308271000010
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/8013
Collection数字内容技术与服务研究中心_听觉模型与认知计算
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Telecom ParisTech, LTCI, CNRS, ENST, Paris, France
3.Univ Paris 09, CNRS, Ctr Rech Math Decis CEREMADE, UMR 7534, F-75775 Paris 16, France
Recommended Citation
GB/T 7714
Yuan, Fei,Xia, Gui-Song,Sahbi, Hichem,et al. Mid-level features and spatio-temporal context for activity recognition[J]. PATTERN RECOGNITION,2012,45(12):4182-4191.
APA Yuan, Fei,Xia, Gui-Song,Sahbi, Hichem,&Prinet, Veronique.(2012).Mid-level features and spatio-temporal context for activity recognition.PATTERN RECOGNITION,45(12),4182-4191.
MLA Yuan, Fei,et al."Mid-level features and spatio-temporal context for activity recognition".PATTERN RECOGNITION 45.12(2012):4182-4191.
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