Projects per year
Abstract
The problem of learning the class identity of visual objects has received considerable attention recently. With rare exception, all of the work to date assumes low variation in appearance, which limits them to a single depictive style usually photographic. The same object depicted in other styles - as a drawing, perhaps - cannot be identified reliably. Yet humans are able to name the object no matter how it is depicted, and even recognise a real object having previously seen only a drawing. This paper describes a classifier which is unique in being able to learn class identity no matter how the class instances are depicted. The key to this is our proposition that topological structure is a class invariant. Practically, we depend on spectral graph analysis of a hierarchical description of an image to construct a feature vector of fixed dimension. Hence structure is transformed to a feature vector, which can be classified using standard methods. We demonstrate the classifier on several diverse classes.
Original language | English |
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Title of host publication | Structural, Syntactic, and Statistical Pattern Recognition |
Editors | N DaVitoria Lobo, T Kasparis, F Roli, J T Kwok, M Georgiopoulos, G C Anagnostopoulos, M Loog |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 329-338 |
Number of pages | 10 |
Volume | 5342/2008 |
Edition | 5342/2008 |
ISBN (Print) | 978-3-540-89688-3 |
DOIs | |
Publication status | Published - 2008 |
Event | Joint International Workshop on Structural, Syntactic, and Statistical Pattern Recognition - Orlando, FL Duration: 1 Jan 2008 → … |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer-Verlag |
Conference
Conference | Joint International Workshop on Structural, Syntactic, and Statistical Pattern Recognition |
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City | Orlando, FL |
Period | 1/01/08 → … |
Bibliographical note
Proceedings of the Joint International Workshop on Structural, Syntactic, and Statistical Pattern Recognition. Univ Central Florida, Orlando, Florida, USA, 4-16 December 2008Fingerprint
Dive into the research topics of 'Structure Is a Visual Class Invariant'. Together they form a unique fingerprint.Projects
- 1 Finished
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MATCHING AND PAINTING USING GESTALT MODELS
Hall, P. (PI) & Collomosse, J. P. (CoI)
Engineering and Physical Sciences Research Council
1/04/06 → 30/09/09
Project: Research council