A Face Recognition System using Eigenfaces: Performance Analysis
نویسندگان
چکیده
منابع مشابه
Face Recognition using Eigenfaces
We tried to develop a real time face detection and recognition system which uses an "appearance-based" approach. For detection purpose we used Viola Jones algorithm. To recognize face we worked with Eigen Faces which is a PCA based algorithm. In a real time to recognize a face we need a data training set. For data training set we took five images of each person and manipulated the Eig...
متن کاملFace Recognition Using Eigenfaces
In this paper we discuss some problem of Eigenfaces which is ignores in the previous work that is the question of which features are important for classification, and which are not. Eigenfaces seeks to answer this by using principal component analysis of the images of the faces. This analysis reduces the dimensionality of the training set, leaving only those features that are critical for face ...
متن کاملFace Recognition Machine Vision System Using Eigenfaces
Face Recognition is a common problem in Machine Learning. This technology has already been widely used in our lives. For example, Facebook can automatically tag people’s faces in images, and also some mobile devices use face recognition to protect private security. Face images comes with different background, variant illumination, different facial expression and occlusion. There are a large num...
متن کاملFace recognition using eigenfaces
We present an approach t o the detection and identification of human faces and describe 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. Our approach treats face recognition as a two-dimensional recognition problem, taking advantage of the fact that faces are are...
متن کاملFace Recognition Using Kernel Eigenfaces
Eigenface or Principal Component Analysis (PCA) methods have demonstrated their success in face recognition, detection, and tracking. The representation in PCA is based on the second order statistics of the image set, and does not address higher order statistical dependencies such as the relationships among three or more pixels. Recently Higher Order Statistics (HOS) have been used as a more in...
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ژورنال
عنوان ژورنال: Journal of Korean Institute of Intelligent Systems
سال: 2005
ISSN: 1976-9172
DOI: 10.5391/jkiis.2005.15.4.400