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Volumn , Issue , 2009, Pages 865-872

Non-negative matrix factorization of partial track data for motion segmentation

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE POINT; HOPKINS; LOCAL VELOCITY; MOTION COMPONENTS; MOTION SEGMENTATION; MULTIPLE MOTIONS; NONNEGATIVE MATRIX FACTORIZATION; REAL-WORLD; SPECTRAL CLUSTERING; TRACK DATA; VELOCITY PROFILES;

EID: 77953177672     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459311     Document Type: Conference Paper
Times cited : (45)

References (21)
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    • H.Shum, K. Ikeuchi, and R. Reddy. Principal component analysis with missing data and its application to polyhedral object modeling. Modelling from reality, pages 3-39, 2001.
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    • Shum, H.1    Ikeuchi, K.2    Reddy, R.3
  • 7
    • 0033284812 scopus 로고    scopus 로고
    • Motion segmentation based on factorization method and discriminant criterion
    • N. Ichimura. Motion segmentation based on factorization method and discriminant criterion. IEEE International Conference on Computer Vision, pages 600-605, 1999.
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    • Ichimura, N.1
  • 8
    • 0034843849 scopus 로고    scopus 로고
    • Motion segmentation by subspace separation and model selection
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    • H. Kim and H. Park. Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis. Bioinformatics, 3(12):1495-1502, 2007.
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    • Kim, H.1    Park, H.2
  • 10
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
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    • Lee, D.D.1    Seung, H.S.2
  • 20
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    • A general framework for motion segmentation: Independent, articulated, rigid, non-rigid, degenerate and non-degenerate
    • J. Yan and M. Pollefeys. A general framework for motion segmentation: Independent, articulated, rigid, non-rigid, degenerate and non-degenerate. In European Conference on Computer Vision, pages 94-106, 2006.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.