Publications:Face authentication with Gabor information on deformable graphs

From ISLAB/CAISR
Revision as of 21:21, 20 June 2017 by Slawek (talk | contribs) (Created page with "<div style='display: none'> == Do not edit this section == </div> {{PublicationSetupTemplate|Author=Benoıt Duc, Stefan Fischer, Josef Bigun |PID=408425 |Name=Duc, Benoıt (Mo...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigationJump to search

Do not edit this section

Property "Publisher" has a restricted application area and cannot be used as annotation property by a user. Property "Author" has a restricted application area and cannot be used as annotation property by a user. Property "Author" has a restricted application area and cannot be used as annotation property by a user. Property "Author" has a restricted application area and cannot be used as annotation property by a user.

Keep all hand-made modifications below

Title Face authentication with Gabor information on deformable graphs
Author
Year 1999
PublicationType Journal Paper
Journal IEEE Transactions on Image Processing
HostPublication
Conference
DOI http://dx.doi.org/10.1109/83.753738
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:408425
Abstract

Elastic graph matching has been proposed as a practical implementation of dynamic link matching, which is a neural network with dynamically evolving links between a reference model and an input image. Each node of the graph contains features that characterize the neighborhood of its location in the image. The elastic graph matching usually consists of two consecutive steps, namely a matching with a rigid grid, followed by a deformation of the grid, which is actually the elastic part. The deformation step is introduced in order to allow for some deformation, rotation, and scaling of the object to be matched. This method is applied here to the authentication of human faces where candidates claim an identity that is to be checked. The matching error as originally suggested is not powerful enough to provide satisfying results in this case. We introduce an automatic weighting of the nodes according to their significance. We also explore the significance of the elastic deformation for an application of face-based person authentication. We compare performance results obtained with and without the second matching step. Results show that the deformation step slightly increases the performance, but has lower influence than the weighting of the nodes. The best results are obtained with the combination of both aspects. The results provided by the proposed method compare favorably with two methods that require a prior geometric face normalization, namely the synergetic and eigenface approaches