Model indexing: the graph-hashing approach

by: H Sossa, R Horaud

Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on (1992), pp. 811-814.

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Abstract

The problem of object recognition in computer vision is addressed. A method for model indexing, which, given a group of image features, rapidly extracts from the list of objects those objects containing this group of features, is presented. The method operates on an abstract representation of features, more precisely, groups of features. In practice, this abstract representation takes the form of a graph. The present study deals with binary graphs only, that is, only one feature-type and one feature-relationship-type can be embedded in the representation

@inproceedings{citeulike:2064921, abstract = {The problem of object recognition in computer vision is addressed. A method for model indexing, which, given a group of image features, rapidly extracts from the list of objects those objects containing this group of features, is presented. The method operates on an abstract representation of features, more precisely, groups of features. In practice, this abstract representation takes the form of a graph. The present study deals with binary graphs only, that is, only one feature-type and one feature-relationship-type can be embedded in the representation}, author = {Sossa, H. and Horaud, R. }, booktitle = {Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on}, citeulike-article-id = {2064921}, journal = {Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on}, keywords = {graph, hash, indexing}, pages = {811--814}, posted-at = {2007-12-06 03:07:42}, priority = {0}, title = {Model indexing: the graph-hashing approach}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=223252}, year = {1992} }

RIS record

TY - CONF ID - citeulike:2064921 L3 - citeulike-article-id:2064921 TI - Model indexing: the graph-hashing approach T2 - Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on JF - Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on SP - 811 EP - 814 N2 - The problem of object recognition in computer vision is addressed. A method for model indexing, which, given a group of image features, rapidly extracts from the list of objects those objects containing this group of features, is presented. The method operates on an abstract representation of features, more precisely, groups of features. In practice, this abstract representation takes the form of a graph. The present study deals with binary graphs only, that is, only one feature-type and one feature-relationship-type can be embedded in the representation KW - graph KW - hash KW - indexing AU - Sossa, H AU - Horaud, R PY - 1992/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=223252 ER -

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