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Resampling for Face Recognition
2003A number of applications require robust human face recognition under varying environmental lighting conditions and different facial expressions, which considerably vary the appearance of human face. However, in many face recognition applications, only a small number of training samples for each subject are available; these samples are not able to ...
Xiaoguang Lu, Anil K. Jain 0001
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Reconstructed Face Recognition
2019Computer-aided craniofacial reconstruction technology has very important application in the field of criminal investigation. But reconstruction a face from skull is not the end of work. The reconstructed face needs to be automatically identified in the missing population photo database.
Xiaoning Liu 0001 +4 more
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Discriminative Face Recognition
2003A novel probabilistic deformable model of face mapping was recently introduced and successfully applied to automatic person identification. In this paper, we consider the use of discrimination to improve the performance of this system. It is possible to introduce discriminative information at two different levels: 1) in the face representations and 2 ...
Florent Perronnin, Jean-Luc Dugelay
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Components for face recognition
Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings., 2004We present a method for automatically learning a set of discriminatory facial components for face recognition. The algorithm performs an iterative growing of components starting with small initial components located around pre-selected points in the face.
Bernd Heisele, Takamasa Koshizen
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2015
This paper presents a method for recognition of infrared images of faces. In this paper, we propose two steps to realize the recognition faces based on InfraRed images. Firstly, find out the signature in face infrared face thermograms using marphological operations. Secondly, measure the texture parameters of face regions.
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This paper presents a method for recognition of infrared images of faces. In this paper, we propose two steps to realize the recognition faces based on InfraRed images. Firstly, find out the signature in face infrared face thermograms using marphological operations. Secondly, measure the texture parameters of face regions.
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Hypnosis and Recognition of a Face
Perceptual and Motor Skills, 198213 hypnotically susceptible subjects were given a hypnotic induction procedure with suggestions to facilitate recognition of a target face shown 7 days earlier. Their accuracy was compared with that of 12 subjects in an untreated control condition. There was no support for the hypothesis that hypnosis improves facial recognition; indeed, there was ...
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3rd International Workshop on Biometrics and Forensics (IWBF 2015), 2015
The facial imagery usually at the disposal for forensics investigations is commonly of a poor quality due to the unconstrained settings in which it was acquired. The captured faces are typically non-frontal, partially occluded and of a low resolution, which makes the recognition task extremely difficult.
Vitomir Struc +2 more
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The facial imagery usually at the disposal for forensics investigations is commonly of a poor quality due to the unconstrained settings in which it was acquired. The captured faces are typically non-frontal, partially occluded and of a low resolution, which makes the recognition task extremely difficult.
Vitomir Struc +2 more
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2013 International Conference on IT Convergence and Security (ICITCS), 2013
In recent years, more and more studies or industry products have conducted recognition to the physiological feature or behavioral expression which are peculiar to human body, and these techniques provide the optimum solution for the environment, which needs identity verification, access badges or high security.
Lawrence Y. Deng +2 more
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In recent years, more and more studies or industry products have conducted recognition to the physiological feature or behavioral expression which are peculiar to human body, and these techniques provide the optimum solution for the environment, which needs identity verification, access badges or high security.
Lawrence Y. Deng +2 more
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2015
What the reader should know to understand this chapter \(\bullet \) Basic notions of image processing (Chap. 3). \(\bullet \) Support vectors machines and kernel methods (Chap. 9). \(\bullet \) Principal component analysis (Chap. 11).
CAMASTRA, Francesco +1 more
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What the reader should know to understand this chapter \(\bullet \) Basic notions of image processing (Chap. 3). \(\bullet \) Support vectors machines and kernel methods (Chap. 9). \(\bullet \) Principal component analysis (Chap. 11).
CAMASTRA, Francesco +1 more
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Synthesizing for face recognition
2011 18th IEEE International Conference on Image Processing, 2011Pose variance is one of the most challenging problem to 2D face recognition. In this paper, a novel frontal view face synthesizing strategy is introduced to improve the performance of traditional face recognition methods on non-frontal view input images.
Yuelong Li, Jufu Feng
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