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

Albarelli, A.; Bergamasco, F.; Rossi, L.; Vascon, S. and Torsello, A. A stable graph-based representation for object recognition through high-order matching. IN: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012). International conference on pattern recognition . IEEE.

Abstract

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.

Divisions: Engineering & Applied Sciences
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Event Title: 21st International Conference on Pattern Recognition
Event Type: Other
Event Dates: 2012-11-11 - 2012-11-15
Uncontrolled Keywords: Computer Vision and Pattern Recognition

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