The quantitative characterization of the distinctiveness and robustness of local image descriptors-Reference-Cited by-同舟云学术

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The quantitative characterization of the distinctiveness and robustness of local image descriptors

Published:2009-07 Issue:8 Volume:27 Page:1143-1156
ISSN:0262-8856
Container-title:Image and Vision Computing
language:en
Short-container-title:Image and Vision Computing

Author:

Carneiro Gustavo,Jepson Allan D.

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing

Reference41 articles.

1. S. Agarwal, D. Roth, Learning a sparse representation for object detection, in: European Conference on Computer Vision, 2002, pp. 113–130.

2. A computational model for visual selection;Amit;Neural Computation,1999

3. A. Bosch, A. Zisserman, X. Munos, Image classification using random forests, in: Proceedings of the International Conference on Computer Vision, Rio de Janeiro, Brazil, 2007.

4. G. Carneiro, D. Lowe, Sparse flexible models of local features, in: European Conference on Computer Vision, Graz, Austria, vol. 3, 2006, pp. 29–43.

5. G. Carneiro, A. Jepson, Phase-based local features, in: European Conference on Computer Vision, Copenhagen, Denmark, 2002, pp. 282–296.

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