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Journal ArticleDOI

Face recognition technology: security versus privacy

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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.

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Citations
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Journal ArticleDOI

Engineering Privacy by Design: Are engineers ready to live up to the challenge?

TL;DR: In this article, the authors interviewed six senior engineers who work for globally leading IT corporations and research institutions to investigate their motivation and ability to comply with privacy regulations, and they pointed out a lack of perceived responsibility, control, autonomy, and frustrations with interactions with the legal world.
Proceedings ArticleDOI

An ethics and security course for students in computer science and information technology

TL;DR: An undergraduate course in computer security that has a strong ethical component and a great emphasis on encouraging student creativity is described.

Human face recognition

TL;DR: A new method for illumination invariant feature extraction based on the illumination-reflectance model is proposed which is computationally efficient and does not require any prior information about the face model or illumination.
Journal ArticleDOI

Face Detection and Recognition System for Enhancing Security Measures Using Artificial Intelligence System

TL;DR: It has been presented that face detection with voice and biometric technology can enhance the security measures and Employee’s attendance can be marked by simply detecting face that can increase punctuality.
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.
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