Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29644


Select areas to restrict search in scientific publication database:
7504
Low Resolution Face Recognition Using Mixture of Experts
Abstract:
Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this paper we introduce a new low resolution face recognition system based on mixture of expert neural networks. In order to produce the low resolution input images we down-sampled the 48 × 48 ORL images to 12 × 12 ones using the nearest neighbor interpolation method and after that applying the bicubic interpolation method yields enhanced images which is given to the Principal Component Analysis feature extractor system. Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in low resolution face recognition that is the recognition rate of 100% for the training set and 96.5% for the test set.
Digital Object Identifier (DOI):

References:

[1] A. Iranzad, S. Masoudnia, F. Cheraghchi, A. Nowzari-Dalini, R. Ebrahimpour, in Proceedings of International Conference on Soft Computing and Pattern Recognition, IEEE Press, Paris, France, pp. 309-313, 2010.
[2] R. Abiantun, M. Savvides, and B. V. K. Vijaya Kumar, How low can you go? low resolution face recognition study using kernel correlation feature analysis on the FRGCv2 dataset, in Special Session on Research at the Biometric Consortium Conference, IEEE Press, New York, NY, USA, pp. 1-6, 2006
[3] S. Baker and T. Kanade, Hallucinating faces, in Proceedings of 14th IEEE Conference on Automatic Face and Gesture Recognition, IEEE Press, Los Alamitos, CA, USA, pp. 83-88, 2000.
[4] H. Chang, D. Yeung, and Y. Xiong, Super-resolution through neighbor embedding, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE Press, Los Alamitos, CA, USA, pp. 275-282, 2004.
[5] C. Conde, A. Ruiz, and E. Cabello, PCA vs low resolution images in face verification, in Proceedings of 12th International Conference on Image Analysis and Processing, IEEE Press, Los Alamitos, CA, USA, pp. 63-67, 2003.
[6] R. Ebrahimpour, E. Kabir, and M.R Yousefi, Teacher-directed learning in view-independent face recognition with mixture of experts using overlapping eigenspaces, Computer Vision and Image Understanding, 111, 2008, 195-206.
[7] W. Freeman, E. Pasztor, and O. Carmichael, Learning low-level vision, International Journal of Computer Vision, 40, 2000, 25-47.
[8] S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice Hall, Ontario, Canada, 1999.
[9] P.H. Hennings-Yeomans, S. Baker, and B.V.K. Vijaya Kumar, Recognition of low-resolution faces using multiple still images and multiple cameras, in Proceeding of 2th IEEE Conference on Biometrics: Theory, Applications and Systems, IEEE Press, New York, NY, USA, pp. 1-6, 2008.
[10] A.N. Htwe, Image Interpolation framework using non-adaptive approach and NL means, International Journal of Network and Mobile Technologies, 1, 2010, 28-32.
[11] I.T. Jolliffe, Principal Component Analysis, Springer-Verlag, New York, NY, USA, 2002.
[12] B. Li, H. Chang, S. Shan, and X. Chen, Low-resolution face recognition via coupled locality preserving mappings, IEEE Signal Processing Letters, 17, 2010, 20-23.
[13] B. Li, H. Chang, S. Shan, X. Chen, and W. Gao, Hallucinating facial images and features, in Proceedings of 19th International Conference on Pattern Recognition, IEEE Press, New York, NY, USA, pp. 1-4, 2008.
[14] C. Liu, H. Shum, and C. Zhang, A two-step approach to hallucinating faces: Global parametric model and local nonparametric model, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE Press, Los Alamitos, CA, USA, pp. 192-198, 2001.
Vol:13 No:05 2019Vol:13 No:04 2019Vol:13 No:03 2019Vol:13 No:02 2019Vol:13 No:01 2019
Vol:12 No:12 2018Vol:12 No:11 2018Vol:12 No:10 2018Vol:12 No:09 2018Vol:12 No:08 2018Vol:12 No:07 2018Vol:12 No:06 2018Vol:12 No:05 2018Vol:12 No:04 2018Vol:12 No:03 2018Vol:12 No:02 2018Vol:12 No:01 2018
Vol:11 No:12 2017Vol:11 No:11 2017Vol:11 No:10 2017Vol:11 No:09 2017Vol:11 No:08 2017Vol:11 No:07 2017Vol:11 No:06 2017Vol:11 No:05 2017Vol:11 No:04 2017Vol:11 No:03 2017Vol:11 No:02 2017Vol:11 No:01 2017
Vol:10 No:12 2016Vol:10 No:11 2016Vol:10 No:10 2016Vol:10 No:09 2016Vol:10 No:08 2016Vol:10 No:07 2016Vol:10 No:06 2016Vol:10 No:05 2016Vol:10 No:04 2016Vol:10 No:03 2016Vol:10 No:02 2016Vol:10 No:01 2016
Vol:9 No:12 2015Vol:9 No:11 2015Vol:9 No:10 2015Vol:9 No:09 2015Vol:9 No:08 2015Vol:9 No:07 2015Vol:9 No:06 2015Vol:9 No:05 2015Vol:9 No:04 2015Vol:9 No:03 2015Vol:9 No:02 2015Vol:9 No:01 2015
Vol:8 No:12 2014Vol:8 No:11 2014Vol:8 No:10 2014Vol:8 No:09 2014Vol:8 No:08 2014Vol:8 No:07 2014Vol:8 No:06 2014Vol:8 No:05 2014Vol:8 No:04 2014Vol:8 No:03 2014Vol:8 No:02 2014Vol:8 No:01 2014
Vol:7 No:12 2013Vol:7 No:11 2013Vol:7 No:10 2013Vol:7 No:09 2013Vol:7 No:08 2013Vol:7 No:07 2013Vol:7 No:06 2013Vol:7 No:05 2013Vol:7 No:04 2013Vol:7 No:03 2013Vol:7 No:02 2013Vol:7 No:01 2013
Vol:6 No:12 2012Vol:6 No:11 2012Vol:6 No:10 2012Vol:6 No:09 2012Vol:6 No:08 2012Vol:6 No:07 2012Vol:6 No:06 2012Vol:6 No:05 2012Vol:6 No:04 2012Vol:6 No:03 2012Vol:6 No:02 2012Vol:6 No:01 2012
Vol:5 No:12 2011Vol:5 No:11 2011Vol:5 No:10 2011Vol:5 No:09 2011Vol:5 No:08 2011Vol:5 No:07 2011Vol:5 No:06 2011Vol:5 No:05 2011Vol:5 No:04 2011Vol:5 No:03 2011Vol:5 No:02 2011Vol:5 No:01 2011
Vol:4 No:12 2010Vol:4 No:11 2010Vol:4 No:10 2010Vol:4 No:09 2010Vol:4 No:08 2010Vol:4 No:07 2010Vol:4 No:06 2010Vol:4 No:05 2010Vol:4 No:04 2010Vol:4 No:03 2010Vol:4 No:02 2010Vol:4 No:01 2010
Vol:3 No:12 2009Vol:3 No:11 2009Vol:3 No:10 2009Vol:3 No:09 2009Vol:3 No:08 2009Vol:3 No:07 2009Vol:3 No:06 2009Vol:3 No:05 2009Vol:3 No:04 2009Vol:3 No:03 2009Vol:3 No:02 2009Vol:3 No:01 2009
Vol:2 No:12 2008Vol:2 No:11 2008Vol:2 No:10 2008Vol:2 No:09 2008Vol:2 No:08 2008Vol:2 No:07 2008Vol:2 No:06 2008Vol:2 No:05 2008Vol:2 No:04 2008Vol:2 No:03 2008Vol:2 No:02 2008Vol:2 No:01 2008
Vol:1 No:12 2007Vol:1 No:11 2007Vol:1 No:10 2007Vol:1 No:09 2007Vol:1 No:08 2007Vol:1 No:07 2007Vol:1 No:06 2007Vol:1 No:05 2007Vol:1 No:04 2007Vol:1 No:03 2007Vol:1 No:02 2007Vol:1 No:01 2007