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Volumn 6, Issue 2013, 2013, Pages 104-110

Detection of activities and events without explicit categorization

Author keywords

Cubic higher order local auto correlation; Direct density ratio estimation; Event detection

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; PROBABILITY;

EID: 84877688785     PISSN: None     EISSN: 18826660     Source Type: Journal    
DOI: 10.2197/ipsjtrans.6.104     Document Type: Article
Times cited : (4)

References (28)
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    • Kawahara, Y.1    Sugiyama, M.2
  • 10
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    • Kobayashi, T. and Otsu, N.: Action and simultaneous multiple-person identification using cubic higher-order local auto-correlation, Proc. 17th International Conference on Pattern Recognition, pp. 741-744 (2004).
    • (2004) Proc. 17th International Conference on Pattern Recognition , pp. 741-744
    • Kobayashi, T.1    Otsu, N.2
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    • Unsupervised learning of human action categories using spatial-temporal words
    • Niebles, J., Wang, H. and Fei-Fei, L.: Unsupervised learning of human action categories using spatial-temporal words, International Journal of Computer Vision, Vol. 79, No. 3, pp. 299-318 (2008).
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    • Spatiotemporal features for action recognition and salient event detection
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    • Unsupervised abnormal behavior detection for real-time surveillance using observed history
    • Yu, T.-H. and Moon, Y.-S.: Unsupervised abnormal behavior detection for real-time surveillance using observed history, Proc. IAPR Conference on Machine Vision Applications, pp. 9-16 (2010).
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.