Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study-Reference-Cited by-同舟云学术

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Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study

Published:2006-09-25 Issue:2 Volume:73 Page:213-238
ISSN:0920-5691
Container-title:International Journal of Computer Vision
language:en
Short-container-title:Int J Comput Vision

Author:

Zhang J.,Marszałek M.,Lazebnik S.,Schmid C.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s11263-006-9794-4.pdf

Reference63 articles.

1. Agarwal, S. and Roth, D. 2002. Learning a sparse representation for object detection. In European Conference on Computer Vision, Vol. 4, pp. 113–130.

2. Berg, A., Berg, T., and Malik, J. 2005. Shape matching and object recognition using low distortion correspondences. In IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. 26–33.

3. Brodatz, P. 1966. Textures: A Photographic Album for Artists and Designers. Dover: New York.

4. Caputo, B., Wallraven, C., and Nilsback, M.-E. 2004. Object categorization via local kernels. In International Conference on Pattern Recognition, Vol. 2, pp. 132–135.

5. Chapelle, O., Haffner, P., and Vapnik, V. 1999. Support vector machines for histogram-based image classification. IEEE Transactions on Neural Networks, 10(5):1055–1064.

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