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Linear Algebra in Facial Recognition by RAJ JAISWAL is a document available to read on EtoBox.

What is Linear Algebra in Facial Recognition about?

- The document discusses applications of linear algebra, specifically principal component analysis (PCA) and eigenfaces, for facial recognition. - PCA and eigenfaces are commonly used linear subspace methods that represent faces as weighted sums of eigenfaces in a lower-dimensional face space. - The mathematics of PCA and eigenfaces for facial recognition are described, including computing the mean face, eigenvectors of the covariance matrix to form the eigenfaces, and projecting faces onto this face space

Author

RAJ JAISWAL

Language

EN