Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study
Top Cited Papers
- 25 September 2006
- journal article
- research article
- Published by Springer Nature in International Journal of Computer Vision
- Vol. 73 (2), 213-238
- https://doi.org/10.1007/s11263-006-9794-4
Abstract
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This publication has 47 references indexed in Scilit:
- Compact representation of bidirectional texture functionsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Shape Matching and Object Recognition Using Low Distortion CorrespondencesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object CategoriesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Discriminative Training for Object Recognition Using Image PatchesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Improving a Discriminative Approach to Object Recognition Using Image PatchesLecture Notes in Computer Science, 2005
- Object categorization via local kernelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Learning a Sparse Representation for Object DetectionLecture Notes in Computer Science, 2002
- Support vector machines for histogram-based image classificationIEEE Transactions on Neural Networks, 1999
- Reflectance and texture of real-world surfacesACM Transactions on Graphics, 1999
- Classification of rotated and scaled textured images using Gaussian Markov random field modelsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1991