Object class recognition with many local features

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2004-January, Issue January, 2004, Pages

  Helmer, Scott ^a   Lowe, David G ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION;

CO-OCCURRENCE; LOCAL FEATURE; LOCAL MODEL; LOCAL PARTS; OBJECT CLASS; OBJECT CLASS RECOGNITION; OBJECT CLASSIFICATION; PROBABILISTIC MODELS; RELATIVE LOCATION; STATISTIC MODELING;

MAXIMUM LIKELIHOOD;

EID: 84932607156     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2004.409     Document Type: Conference Paper

References (9)

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3. R. Fergus, P. Perona, and A. Zisserman, 'Object class recognition by unsupervised scale-invariant learning, ' Conference on Compute r Vision and Pattern Recognition, Madison, Wisconsin (2003), pp. 264-271.
4. L. Fei-Fei,R. Fergus,P. Perona A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories International Conference on Computer Vision, Nice, France 2003, 1134-1141.
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6. D.G. Lowe, 'Distinctive image features from scale-invariant keypoints, ' International Journal of Computer Vision, in press (2004).
7. A.R. Pope, D.G. Lowe, ' Probabilistic Models of Appearance for 3-D Object Recognition,' International Journal of Computer Vision, 40(2), pp. 149-167.
8. S. Ullman, M. Vidal-Naquet, and E. Sali, 'Visual features of intermediate complexity and their use in classification, ' Nature Neuroscience, 5(7), (2002), pp. 1-6.
9. M.Weber,M.Welling, and P. Perona, 'Unsupervised learning of models for recognition, ' European Conference on Computer Vision, Dublin, Ireland (2000), pp. 18-32.