Fractal active shape models

Authors:
Polychronis Manousopoulos;Vassileios Drakopoulos;Theoharis Theoharis
Affiliations:
Department of Informatics and Telecommunications, University of Athens, Panepistimioupolis, Athens, Greece;Department of Informatics and Telecommunications, University of Athens, Panepistimioupolis, Athens, Greece;Department of Informatics and Telecommunications, University of Athens, Panepistimioupolis, Athens, Greece
Venue:
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Year:
2007

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Abstract

Active Shape Models often require a considerable number of training samples and landmark points on each sample, in order to be efficient in practice. We introduce the Fractal Active Shape Models, an extension of Active Shape Models using fractal interpolation, in order to surmount these limitations. They require a considerably smaller number of landmark points to be determined and a smaller number of variables for describing a shape, especially for irregular ones. Moreover, they are shown to be efficient when few training samples are available.