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The representation and matching of categorical shape
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
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2006 (English)In: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 103, no 2, 139-154 p.Article in journal (Refereed) Published
Abstract [en]

We present a framework for categorical shape recognition. The coarse shape of an object is captured by a multiscale blob decomposition, representing the compact and elongated parts of an object at appropriate scales. These parts, in turn, map to nodes in a directed acyclic graph, in which edges encode both semantic relations (parent/child) as well as geometric relations. Given two image descriptions, each represented as a directed acyclic graph, we draw on spectral graph theory to derive a new algorithm for computing node correspondence in the presence of noise and occlusion. In computing correspondence, the similarity of two nodes is a function of their topological (graph) contexts.. their geometric (relational) contexts, and their node contents. We demonstrate the approach on the domain of view-based 3-D object recognition.

Place, publisher, year, edition, pages
2006. Vol. 103, no 2, 139-154 p.
Keyword [en]
generic object recognition, shape categorization, graph matching, scale-spaces, spectral graph theory, earth movers distance, subtree problem, curved objects, good algorithm, recognition, attention, spectra, model
Identifiers
URN: urn:nbn:se:kth:diva-15905DOI: 10.1016/j.cviu.2006.05.001ISI: 000239585800005Scopus ID: 2-s2.0-33746037550OAI: oai:DiVA.org:kth-15905DiVA: diva2:333947
Note
QC 20100525Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2017-12-12Bibliographically approved

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