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


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: College of Engineering & Physical 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
ISBN: 978-1-4673-2216-4, 978-4-9906441-0-9
Last Modified: 08 Dec 2023 12:47
Date Deposited: 21 Sep 2015 10:30
Full Text Link: http://ieeexplo ... rnumber=6460880
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2012
Authors: Albarelli, A.
Bergamasco, F.
Rossi, L. (ORCID Profile 0000-0002-6116-9761)
Vascon, S.
Torsello, A.



Version: Accepted Version

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