Results 311 to 320 of about 6,456,473 (363)
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Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 1992
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 faces.
V, Bruce, A M, Burton, I, Craw
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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 faces.
V, Bruce, A M, Burton, I, Craw
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2009
In the modern life, the need for personal security and access control is becoming an important issue. Biometrics is the technology which is expected to replace traditional authentication methods that are easily stolen, forgotten and duplicated. Fingerprints, face, iris, and voiceprints are commonly used biometric features.
Daijin Kim, Jaewon Sung
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In the modern life, the need for personal security and access control is becoming an important issue. Biometrics is the technology which is expected to replace traditional authentication methods that are easily stolen, forgotten and duplicated. Fingerprints, face, iris, and voiceprints are commonly used biometric features.
Daijin Kim, Jaewon Sung
+5 more sources
2016
Face recognition is a sophisticated problem requiring a significant commitment of computer resources. A modern GPU architecture provides a practical platform for performing face recognition in real time. The majority of the calculations of an eigenpicture implementation of face recognition are matrix multiplications.
Alexander Alling +2 more
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Face recognition is a sophisticated problem requiring a significant commitment of computer resources. A modern GPU architecture provides a practical platform for performing face recognition in real time. The majority of the calculations of an eigenpicture implementation of face recognition are matrix multiplications.
Alexander Alling +2 more
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Cost-Sensitive Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Most traditional face recognition systems attempt to achieve a low recognition error rate, implicitly assuming that the losses of all misclassifications are the same. In this paper, we argue that this is far from a reasonable setting because, in almost all application scenarios of face recognition, different kinds of mistakes will lead to different ...
Yin, Zhang, Zhi-Hua, Zhou
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LightFace: A Hybrid Deep Face Recognition Framework
2020 Innovations in Intelligent Systems and Applications Conference (ASYU), 2020Face recognition constitutes a relatively a popular area which has emerged from the rulers of the social media to top universities in the world. Those frontiers and rule makers recently designed deep learning based custom face recognition models.
Sefik Ilkin Serengil, Alper Ozpinar
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Proceedings of the 2004 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety, 2004. CIHSPS 2004., 2004
This paper describes the developments of the RMA/SIC department in 3D face recognition and situates them in the research activities in this field. 3D face recognition appears as a promising approach for biometric person identification, bringing robust and specific features, with easy face detection from depth and quite difficult faking possibilities ...
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This paper describes the developments of the RMA/SIC department in 3D face recognition and situates them in the research activities in this field. 3D face recognition appears as a promising approach for biometric person identification, bringing robust and specific features, with easy face detection from depth and quite difficult faking possibilities ...
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2009
An overview of selected topics in face recognition is first presented in this chapter. The BioSecure 2D-face Benchmarking Framework is also described, composed of open-source software, publicly available databases and protocols. Three methods for 2D-face recognition, exploiting multiscale analysis, are presented.
M. Tistarelli +7 more
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An overview of selected topics in face recognition is first presented in this chapter. The BioSecure 2D-face Benchmarking Framework is also described, composed of open-source software, publicly available databases and protocols. Three methods for 2D-face recognition, exploiting multiscale analysis, are presented.
M. Tistarelli +7 more
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2007
Face recognition is a task humans perform remarkably easily and successfully. This apparent simplicity was shown to be dangerously misleading as the automatic face recognition seems to be a problem that is still far from solved. In spite of more than 20 years of extensive research, large number of papers published in journals and conferences dedicated ...
Marios Savvides +2 more
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Face recognition is a task humans perform remarkably easily and successfully. This apparent simplicity was shown to be dangerously misleading as the automatic face recognition seems to be a problem that is still far from solved. In spite of more than 20 years of extensive research, large number of papers published in journals and conferences dedicated ...
Marios Savvides +2 more
+5 more sources
2009
Three-dimensional human facial surface information is a powerful biometric modality that has potential to improve the identification and/or verification accuracy of face recognition systems under challenging situations. In the presence of illumination, expression and pose variations, traditional 2D image-based face recognition algorithms usually ...
Gökberk, Berk +5 more
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Three-dimensional human facial surface information is a powerful biometric modality that has potential to improve the identification and/or verification accuracy of face recognition systems under challenging situations. In the presence of illumination, expression and pose variations, traditional 2D image-based face recognition algorithms usually ...
Gökberk, Berk +5 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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