loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
16th International Conference on Pattern Recognition (ICPR'02) - Volume 2
Inexact Graph Matching Using Stochastic Optimization Techniques for Facial Feature Recognition
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
Roberto Cesar, Universidad São Paulo
Endika Bengoetxea, Universidad Basque Country
We propose a formalization of model-based facial feature recognition as an inexact graph matching problem, one graph representing a model of a face and the other an image where recognition has to be performed. The graphs are built from regions and relationships between regions. Both nodes and edges are attributed. A global dissimilarity function is defined based on comparison of attributes of the two graphs, and accounting for the fact that several image regions can correspond to the same model region. This function is then minimized using several stochastic algorithms.
Citation:
Roberto Cesar, Endika Bengoetxea, Isabelle Bloch, "Inexact Graph Matching Using Stochastic Optimization Techniques for Facial Feature Recognition," icpr, vol. 2, pp.20465, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 2, 2002
Usage of this product signifies your acceptance of the Terms of Use.