What are different methods used to achieve facial recognition using artificial intelligence

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What are different methods used to achieve facial recognition using artificial intelligence?
Dec 1, 2018 in Events & Trending Topics by Ali
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2 answers to this question.

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Classical Approach

The classical approach is about choosing features using domain knowledge of the data to create features, which are then classified through a machine learning algorithm.

Modern Approach

The neural network will find features itself. This works on large data sets and is invariant to pose, illuminations, etc. Facebook’s DeepFace and Google’s FaceNet use this approach.

Histogram of Oriented Gradients (HOG)

This technique can spot image gradient or intensity change in localized portions of the image to extract features related to the edges and shapes. HOG features are classified with a Support Vector Machine classifier for face detection.

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answered Dec 1, 2018 by Kailash
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Following method is used for face recognition using Artificial Intelligence:-

Holistic  Approaches 

This approach utilizes global information from faces to perform face recognition. The global data(information) from faces fundamentally show by a small number of features which are directly derived from the pixel of face images. These small numbers of features distinctly capture the variance among different person faces and therefore are used to uniquely identify the person.

Hybrid Approaches.

It is used in both holistic and local features. The concept of eigenfaces can be extended to eigen features, such as eigen eyes, eigen mouth, eigen noise, etc. Since most feature extraction methods have no special requirement on the input feature, it is reasonable to combine it with feature design procedure in order to seek more effective face representation.

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answered Apr 9, 2019 by SA
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