Deforming the blurred shape model for shape description and recognition

Authors:
Jon Almazán;Ernest Valveny;Alicia Fornés
Affiliations:
Computer Vision Center, Dept. Ciències de la Computació, Universitat Autònoma de Barcelona;Computer Vision Center, Dept. Ciències de la Computació, Universitat Autònoma de Barcelona;Computer Vision Center, Dept. Ciències de la Computació, Universitat Autònoma de Barcelona
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

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Abstract

This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance.