Książka Face Recognition & Principal Component Analysis Method Liton Chandra Paul

Face Recognition & Principal Component Analysis Method

Algorithm, Simulation & Discussion

Język: Angielski
Oprawa: Miękka
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
146.40
This book mainly addresses the building of face recognition system and Principal Component Analysis...

Informacje o książce

Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2013
strony
80
EAN
9783659461453
Enbook ID
02201775
Waga
137
Wymiary
150 x 220 x 5

Pełny opis

This book mainly addresses the building of face recognition system and Principal Component Analysis (PCA) method in details. PCA is a statistical approach used for reducing the number of variables in face recognition. In PCA, every image in the training set is represented as a linear combination of weighted eigenvectors called eigenfaces. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a test image onto the subspace spanned by the eigenfaces and then classification is done by measuring Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system. Here, I used a training database of students of ETE-07 series, RUET, Rajshahi-6204, Bangladesh.

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