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Cited by 247

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Face recognition for smart environments

Pentland, A., Choudhury, T.·2000·Computer

Abstract

Smart environments, wearable computers, and ubiquitous computing in general are the coming "fourth generation" of computing and information technology. But that technology will be a stillbirth without new interfaces for interaction, minus a keyboard or mouse. To win wide consumer acceptance, these interactions must be friendly and personalized; the next generation interfaces must recognize people in their immediate environment and, at a minimum, know who they are. In this article, the authors discuss face recognition technology, how it works, problems to be overcome, current technologies, and future developments and possible applications. Twenty years ago, the problem of face recognition was considered among the most difficult in artificial intelligence and computer vision. Today, however, there are several companies that sell commercial face recognition software that is capable of high-accuracy recognition with databases of more than 1,000 people. The authors describe the face recognition technology used, explaining the algorithms for face recognition as well as novel applications, such as behavior monitoring that assesses emotions based on facial expressions.

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Metadata

Authors
Pentland, A., & Choudhury, T.
Venue
Computer
Published
2000
Volume
33
Issue
2
Pages
50-55
ISSN
0018-9162 (ISSN-L)
OpenAlex
W2115943089
Cited by
247
References
2
FWCI
17.53
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Face recognition for smart environments. https://app.cochat.ai/papers/10.1109/2.820039
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Pentland, A., & Choudhury, T. (2000). Face recognition for smart environments. Computer. https://doi.org/10.1109/2.820039

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.