Affine-invariant local descriptors and neighborhood statistics for texture recognition
Lazebnik, S.; Schmid, C.; Ponce, J.
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Volume , Issue , 13-16 Oct. 2003 Page(s):649 - 655 vol.1
Digital Object Identifier   10.1109/ICCV.2003.1238409
Summary:We present a framework for texture recognition based on local affine-invariant descriptors and their spatial layout. At modelling time, a generative model of local descriptors is learned from sample images using the EM algorithm. The EM framework allows the incorporation of unsegmented multitexture images into the training set. The second modelling step consists of gathering co-occurrence statistics of neighboring descriptors. At recognition time, initial probabilities computed from the generative model are refined using a relaxation step that incorporates co-occurrence statistics. Performance is evaluated on images of an indoor scene and pictures of wild animals.

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