A stable graph-based representation for object recognition through high-order matching

A. Albarelli*, F. Bergamasco, L. Rossi, S. Vascon, A. Torsello

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


Many Object recognition techniques perform some flavour of point pattern matching between a model and a scene. Such points are usually selected through a feature detection algorithm that is robust to a class of image transformations and a suitable descriptor is computed over them in order to get a reliable matching. Moreover, some approaches take an additional step by casting the correspondence problem into a matching between graphs defined over feature points. The motivation is that the relational model would add more discriminative power, however the overall effectiveness strongly depends on the ability to build a graph that is stable with respect to both changes in the object appearance and spatial distribution of interest points. In fact, widely used graph-based representations, have shown to suffer some limitations, especially with respect to changes in the Euclidean organization of the feature points. In this paper we introduce a technique to build relational structures over corner points that does not depend on the spatial distribution of the features.

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Pattern Recognition (ICPR2012)
Number of pages4
ISBN (Print)978-1-4673-2216-4 , 978-4-9906441-0-9
Publication statusPublished - 2012
Event21st International Conference on Pattern Recognition - Tsukuba, Japan
Duration: 11 Nov 201215 Nov 2012

Publication series

NameInternational conference on pattern recognition
ISSN (Print)1051-4651


Conference21st International Conference on Pattern Recognition
Abbreviated titleICPR 2012

Bibliographical note

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