Abstract
With the quick grow of multimedia contents, from among this content, face recognition has got a lot of significant, specifically in latest little years. The face as object formed of various recognition characteristics for detect; so, it is still the most challenge research domain for researchers in area of image processing and computer vision. In this survey article, tried to solve the most demanding facial features like illuminations, aging, pose variation, partial occlusion and facial expression. Therefore, it indispensable factors in the system of facial recognition when performed on facial pictures. This paper study the most advanced facial detection techniques too, approaches: Hidden Markov Models, Principal Component Analysis (PCA), Elastic Cluster Plot Matching, Support Vector Machines (SVM), Gabor Waves, Artificial Neural Networks (ANN), Eigen Face, Independent Component Analysis (ICA) and 3D Morphable Model. Additionally to the above works, mentioned various testing facial databases including JAFEE, FEI, Yale, LFW, AT&T(formerly termed as ORL) and AR (Aleix Martinez and Robert Benavente) etc to analyze the results. Even so, the goal of this survey is to present a comprehensive literature review for the face recognition besides its applications after a deepness discussion, some of the experimental results was introduced in the end.
Highlights
The twenty one century is considered a recently and scientific era in which great strides have been made acceleration people in the finishing of their missions
The computers are utilizing in pyramids of the applications that ranging from the simple to the complicated problem-solving ways
The face recognition technological has appeared as a beneficial tool for recognizing features of the faces based on their inherent features
Summary
The twenty one century is considered a recently and scientific era in which great strides have been made acceleration people in the finishing of their missions. In facial recognition systems based 2D fixed picture, a capture of a user is captured and compared to a database of captures to identify a person. Facial pictures in videos are frequently in off-frontal poses and can be subject to significant changes in lighting, which lead decay the performance of majority commercial face recognition systems. A research conducted the latest face recognition technologies, on the standard database (like FAT, FERET, and FRVT) have identified detecting illumination, age and pose as the main issues of the facial recognition algorithm. Since illumination is a factor that considerably affecting of the faces recognition from videos or pictures, the techniques have been development to ignore the impact resulted by this problem [54]. It will not be possible to proxy between friends, as everyone needs a face scan to register its attendance. [56]
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