Face detection -- also called facial detection -- is an artificial intelligence (AI) based computer technology used to find and identify human faces in digital images. ... It now plays an important role as the first step in many key applications -- including face tracking, face analysis and facial recognition.
A general statement of face recognition problem can be formulated as follows: Given still or video images of a scene, identify or verify one or more persons in the scene using a stored database of faces. ... One can broadly classify the challenges Page 3 and techniques into two groups: static and dynamic/video matching.
It is very difficult for a recognition system to identify them. These problems can be due system faults used in face recognition, such as camera distortion, background noise, inefficient storage, improper techniques etc. More than that there can be network problems due to environmental conditions.
There are basically two prevailing approaches to the problem of face recognition namely, Geometric approach i.e. the feature based and the other one is the photometric approach i.e. the view based. As the field of face recognition fascinated many researchers resulting which there were many contrasting algorithms developed, out of which three of them have been widely studied in the literature of face recognition
1) Geometric:
This approach mainly deals with the spatial correlation uniting the profile (i.e. face) features, also we can simply that dimensional layout of the facial attributes. Some of the main geometrical attributes of a human face are nose, eyes and the mouth. Based on these attributes firstly the face is categorized and then based on these attributes respective spatial intervals and the respective associated gradients are estimated, thereby advancing the process of face recognition.
2) Photometric stereo:
It is a methodology of computer vision technology which mainly recuperates the structure of an underlying object from the images that were shot in varying circumstances that were affected by the lighting environment.
![PDF] Using Photometric Stereo for Face Recognition | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/b9696bdba6e16959258bad17ce26e6a643be5faf/2-Figure2-1.png)
Eigen face method
Eigen Face Method (EFM): Kohonen took the initiative of implementing the Eigen vectors for the problem of face recognition, by making use of simple neural network; for recognizing a human face in aligned andnormalized position. Further advancement in this was done by Kirby and Sirovich by making use of Linear Encoding. A vector of size m*n represent the images and then the mean square error is minimized.
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