A Review paper on different Pose Invariant Face Recognition Techniques using Neural Networks

Authors

  • Verma N Computer Science Department ,Maulana Azad National Institue of Technology, Bhopal, MP, India
  • Shukla S Computer Science Department ,Maulana Azad National Institue of Technology, Bhopal, MP, India

Keywords:

Face Recognition, Pose Invariant, Gabor Feature, Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Neural Networks, Classifier

Abstract

In existing face recognition techniques researchers have encountered major difficulties while dealing with variation of poses, aging, expressions, and variation in illumination. As the rotations of face parts causes major differences in face image and changes in appearance. For that reason extensive efforts have been taken by vision researchers in area of pose-invariant face recognition in last decade and many salient methodologies have been implemented. This paper provides a literature review of the existing robust face recognition methodologies using neural networks for handling pose invariant and above mentioned issues which caused difficulties in face recognition, it also contains detailed description of presented methods. This paper also includes strengths and drawbacks of these face recognition systems, and several promising directions for future research are also considered.

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Published

2015-05-30

How to Cite

[1]
N. Verma and S. Shukla, “A Review paper on different Pose Invariant Face Recognition Techniques using Neural Networks”, Int. J. Comp. Sci. Eng., vol. 3, no. 5, pp. 98–104, May 2015.

Issue

Vol. 3 No. 5 (2015): IJCSE May Edition

Section

Review Article

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