DocumentCode :
3212748
Title :
Video-based face recognition using manifold learning by neural networks
Author :
Hamedani, Kian ; Salehi, Seyyed Ali Seyyed
Author_Institution :
Biomed. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran
fYear :
2012
fDate :
15-17 May 2012
Firstpage :
789
Lastpage :
793
Abstract :
This paper proposes a method using manifold learning by neural networks for identifying people while they are talking. In training phase people say the same sentence, we train the NN for learning low-dimensional nonlinear manifolds that are embedded in high-dimensional video space. After training phase we use another video of the same persons while they are saying another sentence for testing. Comparing the recognition results with other methods shows that our method outperforms other methods. Finally we achieve 98.4% of recognition rate.
Keywords :
face recognition; learning (artificial intelligence); neural nets; video signal processing; NN; high-dimensional video space; low-dimensional nonlinear manifold learning; neural networks; people identification; video-based face recognition; Artificial neural networks; Hidden Markov models; Manifolds; Principal component analysis; Testing; Videos; Neural Networks; face recognition; manifold; video;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering (ICEE), 2012 20th Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4673-1149-6
Type :
conf
DOI :
10.1109/IranianCEE.2012.6292461
Filename :
6292461
Link To Document :
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