Journal ArticleDOI
Face recognition technology: security versus privacy
TLDR
The interplay of technical and social issues involved in the widespread application of video surveillance for person identification, including face recognition technology, are analyzed.Abstract:
Video surveillance and face recognition systems have become the subject of increased interest and controversy after the September 11 terrorist attacks on the United States. In favor of face recognition technology, there is the lure of a powerful tool to aid national security. On the negative side, there are fears of an Orwellian invasion of privacy. Given the ongoing nature of the controversy, and the fact that face recognition systems represent leading edge and rapidly changing technology, face recognition technology is currently a major issue in the area of social impact of technology. We analyze the interplay of technical and social issues involved in the widespread application of video surveillance for person identification.read more
Citations
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Poisoning and Evasion Attacks Against Deep Learning Algorithms in Autonomous Vehicles
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Anti-spoofing method for fingerprint recognition using patch based deep learning machine
TL;DR: The proposed method used Discriminative Restricted Boltzmann Machines to recognize fingerprints accurately against fabricated materials used for spoofing.
Social Implications of Technology: The Past, the Present, and the Future This paper introduces the IEEE Society on Social Implications of Technology and examinessomeofthecurrenttechnologytrendsandprospectsforthefutureincluding our relationship with computers and the prospects for a transhumanist future.
TL;DR: The IEEE Society on Social Implications of Technology (SSIT) as discussed by the authors reviewed its contributions since its founding in 1982, and surveyed the outlook for certain key technologies that may have signifi- cant social impacts in the future.
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Multimodal biometrics for identity documents ( )
TL;DR: This research report gives the main definitions, properties and the framework of use related to biometricrics, an overview of the main standards developed in the biometric industry and standardisation organisations to ensure interoperability, as well as some of the legal framework and the issues associated to biometrics such as privacy and personal data protection.
Proceedings ArticleDOI
Factors on the sense of privacy in video surveillance
TL;DR: A system architecture of privacy-preserving video surveillance for a community that achieves a good balance between security and privacy is discussed, which supports PriSurv's design principle, which can adapt the personal sense of privacy.
References
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Journal ArticleDOI
Face recognition: A literature survey
TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Journal ArticleDOI
Detecting faces in images: a survey
TL;DR: In this article, the authors categorize and evaluate face detection algorithms and discuss relevant issues such as data collection, evaluation metrics and benchmarking, and conclude with several promising directions for future research.
Journal ArticleDOI
Human and machine recognition of faces: a survey
TL;DR: A critical survey of existing literature on human and machine recognition of faces is presented, followed by a brief overview of the literature on face recognition in the psychophysics community and a detailed overview of move than 20 years of research done in the engineering community.
Journal ArticleDOI
Comparison and combination of ear and face images in appearance-based biometrics
TL;DR: It is found that recognition performance is not significantly different between the face and the ear, for example, 70.5 percent versus 71.6 percent in one experiment and multimodal recognition using both the ear and face results in statistically significant improvement over either individual biometric.
Journal ArticleDOI
Face Recognition in Poor-Quality Video: Evidence From Security Surveillance:
TL;DR: In this article, the authors examined the ability of subjects to identify target people captured by a commercially available video security device and found that subjects who were personally familiar with the targets performed very well at identifying them, but subjects unfamiliar with the target performed very poorly.