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ACM Computing Surveys, 2003
As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past several years. At least two reasons account for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible ...
Wen-Yi Zhao +3 more
exaly +2 more sources
As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past several years. At least two reasons account for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible ...
Wen-Yi Zhao +3 more
exaly +2 more sources
Current Opinion in Neurobiology, 1992
The study of face-selective neurons in the monkey temporal lobe, and face recognition deficits in humans after brain damage have both become very active fields of investigation. Face-selective neurons appear to be members of ensembles for coding faces rather than individual face detectors or grandmother cells.
C G, Gross, J, Sergent
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The study of face-selective neurons in the monkey temporal lobe, and face recognition deficits in humans after brain damage have both become very active fields of investigation. Face-selective neurons appear to be members of ensembles for coding faces rather than individual face detectors or grandmother cells.
C G, Gross, J, Sergent
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2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2002
A transform domain face recognition approach is presented. The DCT is coupled with the HMM to achieve a recognition rate of 100% on ORL face database of 40 subjects with 10 images per subject. The recognition time for ORL database is little over 2 Sec. 5 images of a subject are used to train HMM and remaining 5 are used for recognition test.
KOHIR, VV, DESAI, UB
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A transform domain face recognition approach is presented. The DCT is coupled with the HMM to achieve a recognition rate of 100% on ORL face database of 40 subjects with 10 images per subject. The recognition time for ORL database is little over 2 Sec. 5 images of a subject are used to train HMM and remaining 5 are used for recognition test.
KOHIR, VV, DESAI, UB
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Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 1992
Abstract Much early work in the psychology of face processing was hampered by a failure to think carefully about task demands. Recently our understanding of the processes involved in the recognition of familiar faces has been both encapsulated in, and guided by, functional models of the processes involved in processing and recognizing
V, Bruce, A M, Burton, I, Craw
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Abstract Much early work in the psychology of face processing was hampered by a failure to think carefully about task demands. Recently our understanding of the processes involved in the recognition of familiar faces has been both encapsulated in, and guided by, functional models of the processes involved in processing and recognizing
V, Bruce, A M, Burton, I, Craw
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Pattern Recognition, 2000
Abstract We propose a new technique for direct visual matching of images for the purposes of face recognition and image retrieval, using a probabilistic measure of similarity, based primarily on a Bayesian (MAP) analysis of image differences. The performance advantage of this probabilistic matching technique over standard Euclidean nearest-neighbor ...
Baback Moghaddam +2 more
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Abstract We propose a new technique for direct visual matching of images for the purposes of face recognition and image retrieval, using a probabilistic measure of similarity, based primarily on a Bayesian (MAP) analysis of image differences. The performance advantage of this probabilistic matching technique over standard Euclidean nearest-neighbor ...
Baback Moghaddam +2 more
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Multibiometrics for face recognition
Datenschutz und Datensicherheit - DuD, 2008Fusion is a popular practice to combine multiple sources of biometric information to achieve systems with greater performance and flexibility. In this paper various approaches to fusion within a multibiometrics context are considered and an application to the fusion of 2D and 3D face information is discussed.
Raymond N. J. Veldhuis +2 more
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Current Neurology and Neuroscience Reports, 2013
Functional imaging studies, intracranial recordings, and lesion-deficit correlations in neurological patients have produced unique insights into the cognitive mechanisms and neural substrates of face recognition. In this review, we highlight recent advances in the field and integrate data from these complementary lines of research to propose a ...
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Functional imaging studies, intracranial recordings, and lesion-deficit correlations in neurological patients have produced unique insights into the cognitive mechanisms and neural substrates of face recognition. In this review, we highlight recent advances in the field and integrate data from these complementary lines of research to propose a ...
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Face recognition with occlusion
2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 2015Facial occlusion, such as sunglasses, scarf, mask etc., is one critical factor that affects the performance of face recognition. Unfortunately, faces with occlusion are quite common in the real world, especially in uncooperative scenario. In recent years, regression analysis becomes a hotspot of dealing with face recognition under different ...
Yingcheng Su +3 more
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Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002
3D human face models have been widely used in applications such as facial animation, video compression/coding, augmented reality, head tracking, facial expression recognition, human action recognition, and face recognition. Modeling human faces provides a potential solution to identifying faces with variations in illumination, pose, and facial ...
Rein-Lien Hsu, Anil K. Jain 0001
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3D human face models have been widely used in applications such as facial animation, video compression/coding, augmented reality, head tracking, facial expression recognition, human action recognition, and face recognition. Modeling human faces provides a potential solution to identifying faces with variations in illumination, pose, and facial ...
Rein-Lien Hsu, Anil K. Jain 0001
openaire +1 more source