Please use this identifier to cite or link to this item:
Title: Restoration of Partially Occluded Shapes of Faces Using Neural Networks
Authors: Draganova, Chrisina 
Christodoulou, Chris 
Lanitis, Andreas 
Keywords: Engineering
Category: Arts
Field: Humanities
Issue Date: 2007
Publisher: Springer Berlin / Heidelberg
Source: Computer Recognition Systems
Series/Report no.: Advances in Soft Computing;30/2005
Abstract: One of the major difficulties encountered in the development of face image processing algorithms, is the possible presence of occlusions that hide part of the face images to be processed. Typical examples of facial occlusions include sunglasses, beards, hats and scarves. In our work we address the problem of restoring the overall shape of faces given only the shape presentation of a small part of the face. For this purpose a novel technique which utilizes combination of Hopfield and Multi-Layer Perceptron (MLP) neural networks was used. According to the experimental results it is possible to recover with reasonable accuracy the overall shape of faces even in the case where a substantial part of the shape of a given face is not visible. The presented technique could form the basis for developing face image processing systems capable of dealing with occluded faces.
ISBN: 978-3-540-25054-8
DOI: 10.1007/3-540-32390-2_90
Collaboration : Cyprus University of Technology
Rights: © Springer
Type: Book Chapter
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

CORE Recommender
Show full item record

Page view(s)

Last Week
Last month
checked on May 23, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.