Face recognition using independent component analysis (ICA)

1. How PCA can be used for face recognition?
2. Can we use Resnet for face recognition?
3. Can naive Bayes classifier be used for face recognition?
4. Which technique is best for face recognition?

How PCA can be used for face recognition?

The main idea of using PCA for face recognition is to express the large 1-D vector of pixels constructed from 2-D facial image into the compact principal components of the feature space. This can be called eigenspace projection.

Can we use Resnet for face recognition?

A facial recognition approach based on Resnet 152 v2 has been proposed in this work which has better accuracy than the existing ones. Since we have used the deep Neural networks in our system, hence the features need not to be extracted manually.

Can naive Bayes classifier be used for face recognition?

It is possible to use only one naïve Bayes classifier for face/nonface classification. However, we suspect that classification will improve if an ensemble of many classifiers, which are based on diverse feature extraction techniques, is used.

Which technique is best for face recognition?

The Eigen faces Algorithm is the most commonly used methods in the field of facial recognition.