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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: Six senior engineers interviewed investigated their motivation and ability to comply with privacy regulations point to a lack of perceived responsibility, control, autonomy, and frustrations with interactions with the legal world.
Journal ArticleDOI

Lightweight Privacy-Preserving Ensemble Classification for Face Recognition

TL;DR: This paper proposes a lightweight privacy-preserving adaptive boosting (AdaBoost) classification framework for face recognition (POR) based on the additive secret sharing and edge computing and proves the correctness and security of the protocols by theoretic analysis.
Journal Article

Digital identity

TL;DR: The nature of identification in a digital networked world, as opposed to a paper-based world, is clarified, illustrating the importance of developing policies with recognition of the social implications of technical change.
Dissertation

Reconocimiento e identificación de las personas mediante biometrías estáticas y dinámicas

TL;DR: In this article, the authors investigate the metodologia, potencialidad, and limitación of the sistemas de reconocimiento biometrico.
Journal ArticleDOI

Exploiting Voronoi diagram properties in face segmentation and feature extraction

TL;DR: This paper seeks to present a novel face segmentation and facial feature extraction algorithm for gray intensity images (each containing a single face object) based on the Voronoi diagram, a well-known technique in computational geometry, which generates clusters of intensity values using information from the vertices of the external boundary of Delaunay triangulation.
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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