DocumentCode :
1537177
Title :
Mapping Dynamic Bayesian Networks to \\alpha -Shapes: Application to Human Faces Identification Across Ages
Author :
Bouchaffra, Djamel
Author_Institution :
Center for Dev. of Adv. Technol., Algiers, Algeria
Volume :
23
Issue :
8
fYear :
2012
Firstpage :
1229
Lastpage :
1241
Abstract :
We propose to map a dynamic Bayesian network (DBN) to an ordered family of α -shapes to improve DBNs classification power. This mission is achieved by: 1) embedding a DBN into a topological manifold and 2) applying the α-shape geometric constructor to build hierarchical structures assigned to the DBN. This continuous representation of traditional DBNs as α-shapes allows more information to be obtained about the objects to be classified. These latter are viewed as hierarchies of geometrical objects with different levels of detail. Topological signatures are therefore unraveled and classification accuracy is enhanced. We have applied the proposed formalism to the task of facial identification across ages. Preliminary results demonstrate that the proposed formalism is a powerful tool since it has outperformed some DBN models, the k-NN classifier, and some recent approaches.
Keywords :
belief networks; face recognition; geometry; image classification; α-shape; DBN classification; dynamic Bayesian network mapping; geometrical object; hierarchical structures; human face identification; k-NN classifier; topological signature; Bayesian methods; Face recognition; Feature extraction; Hidden Markov models; Topology; Wavelet transforms; $alpha$-shapes constructor; computational topology; dynamic Bayesian networks (DBNs); face image identification; maximum weighted cut problem; sorting; wavelet transform;
fLanguage :
English
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2162-237X
Type :
jour
DOI :
10.1109/TNNLS.2012.2200261
Filename :
6215055
Link To Document :
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