A connectionist computational method for face recognition

Ahonen, T., Hadid, A. and Pietikainen, M. (2004). Face recognition with local binary patterns, Proceedings of the 8th European Conference on Computer Vision, ECCV 2004, Prague, Czech Republic, pp. 469-481.Search in Google Scholar

Azorín-López, J., Saval-Calvo, M., Fuster-Guilló, A. and Oliver-Albert, A. (2014). A predictive model for recognizing human behaviour based on trajectory representation, Proceedings of the International Joint Conference on Neural Networks, IJCNN 2014, Beijing, China, pp. 1494-1501.Search in Google Scholar

Baltrusaitis, T., Robinson, P. and Morency, L. (2012). 3D constrained local model for rigid and non-rigid facial tracking, Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Providence, RI, USA, pp. 2610-2617.Search in Google Scholar

Bańka, S., Dworak, P. and Jaroszewski, K. (2014). Design of a multivariable neural controller for control of a nonlinear MIMO plant, International Journal of Applied Mathematics and Computer Science 24(2): 357-369, DOI: 10.2478/amcs-2014-0027.10.2478/amcs-2014-0027Search in Google Scholar

Belhumeur, P.N., Jacobs, D.W., Kriegman, D. and Kumar, N. (2011). Localizing parts of faces using a consensus of exemplars, Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Colorado Springs, CO, USA, pp. 545-552.Search in Google Scholar

Best-Rowden, L., Han, H., Otto, C., Klare, B.F. and Jain, A.K. (2014). Unconstrained face recognition: Identifying a person of interest from a media collection, IEEE Transactions on Information Forensics and Security 9(12): 2144-2157.10.1109/TIFS.2014.2359577Search in Google Scholar

Canny, J. (1986). A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6): 679-698.10.1109/TPAMI.1986.4767851Search in Google Scholar

Chen, X., Zhang, C., Dong, F. and Zhou, Z. (2013). Parallelization of elastic bunch graph matching (EBGM) algorithm for fast face recognition, Proceedings of the 2013 IEEE China Summit & International Conference on Signal and Information Processing, Beijing, China, pp. 201-205.Search in Google Scholar

Costa, J.A.F. (2010). Clustering and visualizing SOM results, Proceedings of the 11th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2010, Paisley, UK, pp. 334-343.Search in Google Scholar

Dantone, M., Gall, J., Fanelli, G. and Van Gool, L. (2012). Real-time facial feature detection using conditional regression forests, Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, Providence, RI, USA, pp. 2578-2585.Search in Google Scholar

Di Stefano, L. and Bulgarelli, A. (1999). A simple and efficient connected components labeling algorithm, Proceedings of the International Conference on Image Analysis and Processing, ICIP 1999, Kobe, Japan, pp. 322-327.Search in Google Scholar

En-Naimani, Z., Lazaar, M. and Ettaouil, M. (2014). Hybrid system of optimal self organizing maps and hidden Markov model for Arabic digits recognition, WSEAS Transactions on Systems 13(60): 606-616.Search in Google Scholar

Espí, R., Pujol, F.A., Mora, H. and Mora, J. (2008). Development of a distributed facial recognition system based on graph-matching, Proceedings of the International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2008, Salamanca, Spain, pp. 498-502.Search in Google Scholar

Gao, J. and Fan, L. (2011). Kernel-based weighted discriminant analysis with QR decomposition and its application face recognition, WSEAS Transactions on Mathematics 10(10): 358-367.Search in Google Scholar

Gao, J., Fan, L., Li, L. and Xu, L. (2013a). A practical application of kernel-based fuzzy discriminant analysis, International Journal of Applied Mathematics and Computer Science 23(4): 887-903, DOI: 10.2478/amcs-2013-0066.10.2478/amcs-2013-0066Search in Google Scholar

Gao, J., Fan, L. and Xu, L. (2012). Solving the face recognition problem using QR factorization, WSEAS Transactions on Mathematics 11(8): 728-737.Search in Google Scholar

Gao, J., Fan, L. and Xu, L. (2013b). Median null(sw)-based method for face feature recognition, Applied Mathematics and Computation 219(12): 6410-6419.10.1016/j.amc.2013.01.005Search in Google Scholar

Georghiades, A.S., Belhumeur, P.N. and Kriegman, D.J. (2001). From few to many: Illumination cone models for face recognition under variable lighting and pose, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6): 643-660.10.1109/34.927464Search in Google Scholar

Gocławski, J., Sekulska-Nalewajko, J. and Kuźniak, E. (2012). Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses, International Journal of Applied Mathematics and Computer Science 22(3): 669-684, DOI: 10.2478/v10006-012-0050-5.10.2478/v10006-012-0050-5Search in Google Scholar

González-Jiménez, D. and Alba-Castro, J.L. (2007). Shape-driven Gabor jets for face description and authentication, IEEE Transactions on Information Forensics and Security 2(4): 769-780.10.1109/TIFS.2007.910238Search in Google Scholar

Guo, G., Mu, G. and Ricanek, K. (2010). Cross-age face recognition on a very large database: The performance versus age intervals and improvement using soft biometric traits, Proceedings of the 20th International Conference on Pattern Recognition, ICPR, Istanbul, Turkey, pp. 3392-3395.Search in Google Scholar

Hsu, R.-L., Abdel-Mottaleb, M. and Jain, A.K. (2002). Face detection in color images, IEEE Transactions on Pattern Analysis and Machine Intelligence 24(5): 696-706.10.1109/34.1000242Search in Google Scholar

Huang, G. B., Ramesh, M., Berg, T. and Learned-Miller, E. (2007). Labeled faces in the wild: A database for studying face recognition in unconstrained environments, Technical Report 07-49, University of Massachusetts, Amherst, MA.Search in Google Scholar

Huang, S.M. and Yang, J.F. (2013). Linear discriminant regression classification for face recognition, Signal Processing Letters 20(1): 91-94.10.1109/LSP.2012.2230257Search in Google Scholar

Jin, X., Tan, X. and Zhou, L. (2013). 3D constrained local model for rigid and non-rigid facial tracking, Proceedings of the 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG13, Shanghai, China, pp. 1-8.Search in Google Scholar

Kayarvizhy, N., Kanmani, S. and Uthariaraj, R. (2014). ANN models optimized using swarm intelligence algorithms, WSEAS Transactions on Computers 13(45): 501-519.Search in Google Scholar

Khatun, A. and Bhuiyan, M. (2011). Neural network based face recognition with Gabor filters, International Journal of Computer Science and Network Security 11(1): 71-74.Search in Google Scholar

Kohonen, T. (2001). Self-Organising Maps, 3rd Edition, Springer-Verlag, Berlin/Heidelberg.10.1007/978-3-642-56927-2Search in Google Scholar

Kotropoulos, C. and Pitas, I. (1997). Rule-based face detection in frontal views, IEEE International Conference on Acoustics, Speech, and Signal Processing, Munich, Germany, pp. 2537-2540.Search in Google Scholar

Kumar, A. and Kumar, S. (2015). An improved neural network based approach for identification of self & non-self processes, WSEAS Transactions on Computers 14(28): 272-286.Search in Google Scholar

Lai, Z., Xu, Y., Chen, Q., Yang, J. and Zhang, D. (2014). Multilinear sparse principal component analysis, IEEE Transactions on Neural Networks and Learning Systems 25(10): 1942-1950.10.1109/TNNLS.2013.2297381Search in Google Scholar

Lee, K.-C., Ho, J. and Kriegman, D.J. (2005). Acquiring linear subspaces for face recognition under variable lighting, IEEE Transactions on Pattern Analysis and Machine Intelligence 27(5): 684-698.10.1109/TPAMI.2005.92Search in Google Scholar

Li, J.-B., Chu, S.-C. and Pan, J.-S. (2014). Kernel Learning Algorithms for Face Recognition, Springer, New York, NY.10.1007/978-1-4614-0161-2Search in Google Scholar

Loderer, M., Pavlovicova, J., Feder, M. and Oravec, M. (2014). Data dimension reduction in training strategy for face recognition system, Proceedings of the IEEE 2014 International Conference on Systems, Signals and Image Processing, IWSSIP, Dubrovnik, Croatia, pp. 263-266.Search in Google Scholar

Mitra, S., Parua, S., Das, A. and Mazumdar, D. (2011). A novel datamining approach for performance improvement of EBGM based face recognition system to handle large database, Proceedings of the 1st International Conference on Computer Science and Information Technology, CCSIT 2011, Bangalore, India, pp. 532-541.Search in Google Scholar

Monzo, D., Albiol, A. and Mossi, J.M. (2010). A comparative study of facial landmark localization methods for face recognition using hog descriptors, Proceedings of the 20th International Conference on Pattern Recognition, ICPR, Istanbul, Turkey, pp. 1330-1333.Search in Google Scholar

Murthy, C.A. and Pal, S.K. (1990). Fuzzy thresholding: Mathematical framework, bound functions and weighted moving average technique, Pattern Recognition Letters 11(3): 197-206. 10.1016/0167-8655(90)90006-NSearch in Google Scholar

Phillips, P.J., Moon, H., Rizvi, S.A. and Rauss, P.J. (2000). The FERET evaluation methodology for face recognition algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10): 1090-1104.10.1109/34.879790Search in Google Scholar

Piegat, A. (2005). A new definition of the fuzzy set, International Journal of Applied Mathematics and Computer Science 15(1): 125-140.Search in Google Scholar

Pujol, F., Espí, R., Mora, H. and Sánchez, J. (2008). A fuzzy approach to skin color detection, Proceedings of the 7th Mexican International Conference on Artificial Intelligence, MICAI 2008, Atizapan de Zaragoza, Mexico, pp. 532-542.Search in Google Scholar

Rattani, A., Agarwal, N., Mehrotra, H. and Gupta, P. (2006). An efficient fusion-based classifier, Proceedings of the Workshop on Computer Vision, Graphics and Image Processing, WCVGIP, Hyderabad, India, pp. 104-109.Search in Google Scholar

Sarkar, S. (2012). Skin segmentation based elastic bunch graph matching for efficient multiple face recognition, Proceedings of the 2nd International Conference on Computer Science, Engineering and Applications, ICCSEA 2012, New Delhi, India, pp. 31-40.Search in Google Scholar

Shen, L. and Bai, L. (2006). A review on Gabor wavelets for face recognition, Pattern Analysis and Applications 9(2): 273-292.10.1007/s10044-006-0033-ySearch in Google Scholar

Shin, Y.J. and Park, C.H. (2011). Analysis of correlation based dimension reduction methods, International Journal of Applied Mathematics and Computer Science 21(3): 549-558, DOI: 10.2478/v10006-011-0043-9.10.2478/v10006-011-0043-9Search in Google Scholar

Taigman, Y., Yang, M., Ranzato, M.A., and Wolf, L. (2015). Web-scale training for face identification, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, pp. 2746-2754.Search in Google Scholar

Tran, H.L., Pham, V.N. and Vuong, H.N. (2014). Multiple neural network integration using a binary decision tree to improve the ECG signal recognition accuracy, International Journal of Applied Mathematics and Computer Science 24(3): 647-655, DOI: 10.2478/amcs-2014-0047.10.2478/amcs-2014-0047Search in Google Scholar

Turk, M. and Pentland, A. (1991). Eigenfaces for recognition, Journal of Cognitive Neuroscience 3(1): 71-86.10.1162/jocn.1991.3.1.7123964806Search in Google Scholar

Viola, P. and Jones, M.J. (2004). Robust real-time face detection, International Journal of Computer Vision 57(2): 137-154.10.1023/B:VISI.0000013087.49260.fbSearch in Google Scholar

Vu, N.S. and Caplier, A. (2012). Enhanced patterns of oriented edge magnitudes for face recognition and image matching, IEEE Transactions on Image Processing 21(3): 1352-1365.10.1109/TIP.2011.2166974Search in Google Scholar

Wiskott, L., Fellous, J.-M., Kruger, N. and von der Malsburg, C. (1997). Face recognition by elastic bunch graph matching, IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7): 775-789.10.1109/34.598235Search in Google Scholar

Yang, J., Fu, Z. and Tan, T. (2004). Skin color detection using multiple cues, Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, pp. 632-635.Search in Google Scholar

Yang, M., Zhang, L., Shiu, S.K. and Zhang, D. (2013). Robust kernel representation with statistical local features for face recognition, IEEE Transactions on Neural Networks and Learning Systems 24(6): 900-912.10.1109/TNNLS.2013.2245340Search in Google Scholar

Yin, H. (2008). The self-organizing maps: Background, theories, extensions and applications, in J. Fulcher and L.C.J. Lakhmi (Eds.), Computational Intelligence: A Compendium, Springer-Verlag, Berlin, pp. 715-762.10.1007/978-3-540-78293-3_17Search in Google Scholar

Zadeh, L.A. (1965). Fuzzy sets, Information and Control 8(3): 338-353.10.1016/S0019-9958(65)90241-XSearch in Google Scholar

Zheng, W., Lai, J., Xie, X., Liang, Y., Yuen, P. C. and Zou, Y. (2011). Kernel methods for facial image preprocessing, in P. Wang (Ed.), Pattern Recognition, Machine Intelligence and Biometrics, Springer, Berlin/Heidelberg, pp. 389-409.10.1007/978-3-642-22407-2_16Search in Google Scholar

Zhong, F., Zhang, J. and Li, D. (2014). Discriminant locality preserving projections based on L1-norm maximization, IEEE Transactions on Neural Networks and Learning Systems 25(11): 2065-2074. 10.1109/TNNLS.2014.230379825330429Search in Google Scholar