Face recognition using Eigenfaces

Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. Proposed methodology is connection of two stages -...

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Veröffentlicht in:2011 3rd International Conference on Computer Research and Development Jg. 2; S. 302 - 306
Hauptverfasser: Kshirsagar, V P, Baviskar, M R, Gaikwad, M E
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2011
Schlagworte:
Covariance matrix
Eigen values
Eigenfaces
Eigenvector
Face
Face recognition
Feature extraction
Jacobian matrices
Principal Component Analysis
Training
Vectors
ISBN:1612848397, 9781612848396
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. Proposed methodology is connection of two stages - Feature extraction using Principle Component Analysis and recognition using the feed forward back propagation Neural Network. The goal is to implement the system (model) for a particular face and distinguish it from a large number of stored faces with some real-time variations as well. The Eigenface approach uses Principal Component Analysis (PCA) algorithm for the recognition of the images. It gives us efficient way to find the lower dimensional space.
ISBN:1612848397
9781612848396
DOI:10.1109/ICCRD.2011.5764137