Open Access
Shape Invariant Recognition of Segmented Human Faces using Eigenfaces
TLDR
This paper describes an efficient approach for face recognition as a two step process: 1) segmenting the face region from an image by using an appearance based model, 2) using eigenfaces for person identification for segmented face region.Abstract:
This paper describes an efficient approach for face recognition as a two step process: 1) segmenting the face region from an image by using an appearance based model, 2) using eigenfaces for person identification for segmented face region. The efficiency lies not only in generation of appearance models which uses the explicit approach for shape and texture but also the combined use of the aforementioned techniques. The result is an algorithm that is robust against facial expressions variances. Moreover it reduces the amount of texture up to 12% of the image texture instead of considering whole face image. Experiments have been performed on Cohn Kanade facial database using ten subjects for training and sever for testing purposes. This achieved a successful face recognition rate up to 92.85% with and without facial expressions. Face recognition using Principal Component Analysis (PCA) is fast and efficient to use, while the extracted appearance model can be further used for facial recognition and tracking under lighting and pose variations. This combination is simple to model and apply in real time. KeywordsActive shape models, active appearance models, principal components analysis, eigenfaces, faceread more
Citations
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Spatial tessellations. Concepts and Applications of Voronoi diagrams
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Journal ArticleDOI
Eigen Faces and Principle Component Analysis for Face Recognition Systems: A Comparative Study
TL;DR: A comparative study of literature researches related to Eigenfaces and PCA for face recognition systems and many recommendations were suggested in this study.
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References
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Journal ArticleDOI
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Journal ArticleDOI
Active appearance models
Abstract: We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training set. We construct an efficient iterative matching algorithm by learning the relationship between perturbations in the model parameters and the induced image errors.
Proceedings ArticleDOI
Face recognition using eigenfaces
Matthew Turk,Alex Pentland +1 more
TL;DR: An approach to the detection and identification of human faces is presented, and a working, near-real-time face recognition system which tracks a subject's head and then recognizes the person by comparing characteristics of the face to those of known individuals is described.
Book
Spatial Tessellations: Concepts and Applications of Voronoi Diagrams
TL;DR: In this article, the Voronoi diagram generalizations of the Voroni diagram algorithm for computing poisson Voroni diagrams are defined and basic properties of the generalization of Voroni's algorithm are discussed.