DeepFace: Closing the Gap to Human-Level Performance in Face Verification.
In:
Conference on Computer Vision and Pattern Recognition (CVPR).
2014.
Yaniv Taigman, Ming Yang, Marc'Aurelio Ranzato und Lior Wolf.
[BibTeX]
Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles.
In:
Modeling and Mining Ubiquitous Social Media.
Springer Verlag, Heidelberg, Germany, 2012.
Martin Atzmueller, Stephan Doerfel, Andreas Hotho, Folke Mitzlaff und Gerd Stumme.
[doi]
[BibTeX]
Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles.
In:
Modeling and Mining Ubiquitous Social Media.
Springer Verlag, Heidelberg, Germany, 2012.
Martin Atzmueller, Stephan Doerfel, Andreas Hotho, Folke Mitzlaff und Gerd Stumme.
[BibTeX]
Face-to-Face Contacts during a Conference: Communities, Roles, and Key Players.
In:
Proc. Workshop on Mining Ubiquitous and Social Environments (MUSE 2011) at ECML/PKDD 2011.
2011.
Martin Atzmueller, Stephan Doerfel, Andreas Hotho, Folke Mitzlaff und Gerd Stumme.
[BibTeX]
Face-to-Face Contacts during LWA 2010 - Communities, Roles, and Key Players.
In:
Working Notes of the LWA 2011 - Learning, Knowledge, Adaptation.
2011.
Martin Atzmueller, Stephan Doerfel, Andreas Hotho, Folke Mitzlaff und Gerd Stumme.
[BibTeX]
Face recognition: A literature survey.
ACM Comput. Surv., 35(4):399-458, 2003.
W. Zhao, R. Chellappa, P. J. Phillips und A. Rosenfeld.
[doi]
[Kurzfassung]
[BibTeX]
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 technologies after 30 years of research. Even though current machine recognition systems have reached a certain level of maturity, their success is limited by the conditions imposed by many real applications. For example, recognition of face images acquired in an outdoor environment with changes in illumination and/or pose remains a largely unsolved problem. In other words, current systems are still far away from the capability of the human perception system.This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition, relevant topics such as psychophysical studies, system evaluation, and issues of illumination and pose variation are covered.