A Hierarchical Model for the Recognition of Deformable Objects

Authors:
Martin Stommel;Klaus-Dieter Kuhnert
Affiliations:
Institute of Real-Time Learning Systems, University of Siegen, Siegen, Germany 57076;Institute of Real-Time Learning Systems, University of Siegen, Siegen, Germany 57076
Venue:
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Year:
2008

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Abstract

This paper proposes a hierarchical model for the recognition of deformable objects. Object categories are modelled by multiple views, views in turn consist of several parts, and parts consist of several features. The main advantage of the proposed model is that its nodes can be tuned with regard to the spatial selectivity. Every node in a category, views or part can thus take on the shape of a simple bag of features or a geometrically selective constellation model including all forms in between. Together with the explicit modelling of multiple views this allows for the modelling of categories with high intra-class variance. Experimental results show a high precision for the recognition of a character from a cartoon data base.