Open Access
Facial Recognition using Eigenfaces by PCA
Y. Vijaya Lata,Chandra Kiran Bharadwaj Tungathurthi,H. Ram,Mohan Rao,A. Govardhan,L. P. Reddy +5 more
TLDR
Different face recognition approaches are referred to and primarily focuses on principal component analysis, for the analysis and the implementation is done in free software, Scilab, using SIVP toolbox for performing the image analysis.Abstract:
Face recognition systems have been grabbing high attention from commercial market point of view as well as pattern recognition field. It also stands high in researchers community. Face recognition have been fast growing, challenging and interesting area in real-time applications. A large number of face recognition algorithms have been developed from decades. The present paper refers to different face recognition approaches and primarily focuses on principal component analysis, for the analysis and the implementation is done in free software, Scilab. This face recognition system detects the faces in a picture taken by web-cam or a digital camera, and these face images are then checked with training image dataset based on descriptive features. Descriptive features are used to characterize images. Scilab's SIVP toolbox is used for performing the image analysis. Keywords—eigenfaces, PCA, face recognition, image processing, person identification, face classification, Scilab, SIVPread more
Citations
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Proceedings ArticleDOI
Face recognition using Eigenfaces
TL;DR: The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image using Principle Component Analysis and recognition using the feed forward back propagation Neural Network.
Face Recognition using Principle Component Analysis
Sarala A. Dabhade,M. S. Bewoor +1 more
TL;DR: Their system tries to detect the critical areas of the face using an information theory approach that decomposes face images into a small set of characteristic feature images called „Eigen faces”, which are actually the principal components of the initial training set of face images.
Face recognition using Principal Component Analysis method
TL;DR: This thesis used a training database of students of Electronics and Telecommunication Engineering department, Batch-2007, Rajshahi University of Engineering and Technology, Bangladesh to evaluate the performance of the face recognition system using Principal Component Analysis (PCA).
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Real-time feedback and booking behavior in the hospitality industry: Moderating the balance between imperfect judgment and imperfect prescription
TL;DR: In this article, the authors use a laboratory experiment to investigate how different forms of continuous performance feedback influence agent decisions in a hotel reservation context, considering both a revenue-focused metric and a metric framed around pricing-curve adherence as the basis of two feedback mechanisms of interest.
Proceedings ArticleDOI
Deep Face Recognition for Biometric Authentication
TL;DR: A convolutional neural network based face recognition system which detects faces in an input image using Viola Jones face detector and automatically extracts facial features from detected faces using a pre-trained CNN for recognition.
References
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Face recognition using eigenfaces
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