Abstract
No one can deny the fact that face recognition systems, as one of the most adaptable systems in biometric facial recognition, has interestingly been one of the fields that draw researchers’ attention to enhance the efficiency and efficacy of biometric applications. These researchers have mainly focused on the existed limitations such as extracting unique and differentiable features that are not disturbed by pose, as well as illuminations and other environmental and physical variations. As such, using an Active Appearance Model (AAM) is known to be a solution to extract features by precise modeling of human faces under various physical and environmental circumstances. This research paper tries to draw attention to using AAM based 1 to N face recognition system which the performance of such system can be seen in the experimental results.
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References
Ebrahimpour, R., Jahani, A., Amiri, A., Nazari, M.: Expression-Independent Face Recognition Using Biologically Inspired Features. Indian Journal of Computer Science and Engineering 2(3), 492–499 (2011)
Sudhir, K., Saoni, B.: Face Recognition Using K2DSPCA. In: Proceedings of the International Conference on Information and Network Technology, Singapore, vol. 4, pp. 84–88 (2011)
Patil, A.M., Kolhe, S.R., Patil, P.M.: 2D Face Recognition Techniques: A Survey. International Journal of Machine Intelligence 2(1), 74–83 (2010)
Mini, S.A., Sumit, C.: Effect of Distance Measure. In: PCA Based Face Recognition. International Journal of Enterprise Computing and Business Systems 1(2) (2011)
Hua, G., Hazým, K.E., Mika, F., Rainer, S.: Boosting Pseudo Census Transform Features for Face Alignment. In: Proceedings of BMVC, Dundee, pp. 1–11 (2011)
Dinesh, G.: Application of Active Appearance Model to Automatic Face Replacement. Journal of Applied Statistics (2011)
Patrick, S., Tim, C., Chris, T.: Accurate Regression Procedures for Active Appearance Models. In: BMVC, pp. 1–11 (2011)
Thorsten, G., Andre, G., Rolf-Rainer, G.: Face Recognition Under Pose Variations using Shape-Adapted Texture Features. In: Proceedings of IEEE International Conference on Image Processing, Hong Kong, pp. 4525–4528 (2010)
Thorsten, G., Katerina, A.M., Andre, G., Rolf-Rainer, G.: Facial Pose Estimation using Active Appearance Models and a Generic Face Model. In: Proceedings of the Fifth International Conference on Computer Vision Theory and Applications, Angers, France, vol. 2, pp. 499–506 (2010)
Rabiul, I., Fayzur, R.: Feature and Decision Fusion based Facial Recognition in Challenging Environment. IJCA Journal 6(1), 30–35 (2011)
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Hasan, M., Sheikh Abdullaha, S.N.H., Othman, Z.A. (2013). Efficient Face Recognition Technique with Aid of Active Appearance Model. In: Omar, K., et al. Intelligent Robotics Systems: Inspiring the NEXT. FIRA 2013. Communications in Computer and Information Science, vol 376. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40409-2_9
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DOI: https://doi.org/10.1007/978-3-642-40409-2_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40408-5
Online ISBN: 978-3-642-40409-2
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