Yusof, Rubiyah and M. I., Razzak and M. K., Khan and K., Alghathbar (2010) Face recognition using layered linear discriminant analysis and small subspace. In: Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010, 29 June - 1 July, 2010, Bradford, United Kingdom.
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Official URL: http://dx.doi.org/10.1109/CIT.2010.252
Face recognition has great demands in human recognition and recently it becomes one of the most important research areas of biometrics. In this paper, we present a novel layered face recognition method based on Fisher’s linear discriminant analysis. The basic aim is to decrease FAR by reducing the face dataset to small size by applying layered linear discriminant analysis. Although, the computational complexity at the time of recognition is much higher than conventional PCA and LDA due to the weights computation for small subspace at the time of recognition, but on the other hand the layered LDA provides significant performance gain especially on similar face database. Layered LDA is insensitive to large dataset and also small sample size and it provides 93% accuracy on BANCA face database. Experimental and simulation results show that the proposed scheme has encouraging results for a practical face recognition system.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||biometrics, face recognition, LDA, layered, PCA|
|Subjects:||T Technology > TK Electrical engineering. Electronics Nuclear engineering|
|Deposited By:||Liza Porijo|
|Deposited On:||29 Aug 2012 02:58|
|Last Modified:||08 Feb 2017 00:18|
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