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Volumn , Issue , 2014, Pages 820-826

A multigraph representation for improved unsupervised/semi-supervised learning of human actions

Author keywords

Clustering; Human Action Recognition; Manifold Learning; Multimedia Retrieval; Spectral Embedding; Unsupervised Learning

Indexed keywords

DIRECTED GRAPHS; EMBEDDINGS; GRAPHIC METHODS; PATTERN RECOGNITION; UNSUPERVISED LEARNING;

EID: 84911457884     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.110     Document Type: Conference Paper
Times cited : (39)

References (19)
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    • Niebles, J.C.1    Wang, H.2    Fei-Fei, L.3
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    • Modeling temporal structure of decomposable motion segments for activity classification
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    • Dense trajectories and motion boundary descriptors for action recognition
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    • Discovering motion primitives for unsupervised grouping and one-shot learning of human actions, gestures, and expressions
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.