Study of Face Recognition Techniques: A Survey

With the rapid growth in multimedia contents, among such content face recognition has got much attention especially in past few years. Face as an object consists of distinct features for detection; therefore, it remains most challenging research area for scholars in the field of computer vision and image processing. In this survey paper, we have tried to address most endeavoring face features such as pose invariance, aging, illuminations and partial occlusion. They are considered to be indispensable factors in face recognition system when realized over facial images. This paper also studies state of the art face detection techniques, approaches, viz. Eigen face, Artificial Neural Networks (ANN), Support Vector Machines (SVM), Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor Wavelets, Elastic Bunch Graph Matching, 3D morphable Model and Hidden Markov Models. In addition to the aforementioned works, we have mentioned different testing face databases which include AT & T (ORL), AR, FERET, LFW, YTF, and Yale, respectively for results analysis. However, aim of this research is to provide comprehensive literature review over face recognition along with its applications. And after in depth discussion, some of the major findings are given in conclusion.

@article{Lal2018,
  title     = {Study of Face Recognition Techniques: A Survey},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {6},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Madan Lal and Kamlesh Kumar and Rafaqat Hussain Arain and Abdullah Maitlo and Sadaquat Ali Ruk and Hidayatullah Shaikh},
  doi       = {10.14569/IJACSA.2018.090606},
  url       = {https://doi.org/10.14569/IJACSA.2018.090606}
}