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Journal ArticleDOI

Shadow compensation in 2D images for face recognition

Sang-Il Choi, +2 more
- 01 Jul 2007 - 
- Vol. 40, Iss: 7, pp 2118-2125
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TLDR
The proposed method is simple and requires much less computational effort than the other methods based on 3D models, and at the same time, provides a comparable recognition rate.
About
This article is published in Pattern Recognition.The article was published on 2007-07-01. It has received 51 citations till now. The article focuses on the topics: Three-dimensional face recognition & Facial recognition system.

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Citations
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Journal ArticleDOI

Normalization of Face Illumination Based on Large-and Small-Scale Features

TL;DR: It is argued that both large-and small-scale features of a face image are important for face restoration and recognition, and it is suggested that illumination normalization should be performed mainly on the large-scale featured rather than on the original face image.
Journal ArticleDOI

Extraction of illumination invariant facial features from a single image using nonsubsampled contourlet transform

TL;DR: This paper proposes to utilize the logarithmic nonsubsampled contourlet transform (LNSCT) to estimate the reflectance component from a single face image and refer it as the illumination invariant feature for face recognition, where NSCT is a fully shift-invariant, multi-scale, and multi-direction transform.
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Singular value decomposition and local near neighbors for face recognition under varying illumination

TL;DR: The experimental results indicate that the proposed methods can obtain high performances under different illumination variations and outperform several state-of-the-art approaches which are proposed to address face recognition under varying illumination.
Journal ArticleDOI

A novel hybrid approach based on sub-pattern technique and whitened PCA for face recognition

TL;DR: By simultaneously considering global and local information of face images, a novel hybrid approach which combines PCA II and Sp-PCA I for face recognition is developed which has better recognition performance than that obtained using other traditional methods.
Journal ArticleDOI

Recent development in face recognition

TL;DR: This paper investigates various feature-based automatic face recognition approaches in detail and provides a review of the facial recognition approaches individually dealing with issues of pose, illumination and expression.
References
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Journal ArticleDOI

Eigenfaces for recognition

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.
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Eigenfaces vs. Fisherfaces: recognition using class specific linear projection

TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
Book

Introduction to Statistical Pattern Recognition

TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
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From few to many: illumination cone models for face recognition under variable lighting and pose

TL;DR: A generative appearance-based method for recognizing human faces under variation in lighting and viewpoint that exploits the fact that the set of images of an object in fixed pose but under all possible illumination conditions, is a convex cone in the space of images.
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