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
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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Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Self-citationThe Computer for the 21st Century
Weiser, M. (1991) · Scientific American · doi:10.1038/scientificamerican0991-94 · Cited by 10,017
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Daugman, J. (2004) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2003.818350 · Cited by 2,927
The role of leadership in a digitalized world: a review
Cortellazzo, L., Bruni, E., & Zampieri, R. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01938 · Cited by 808
E-leadership: Re-examining transformations in leadership source and transmission
Avolio, B. J., Sosik, J. J., Kahai, S. S., & Baker, B. (2014) · The Leadership Quarterly · doi:10.1016/j.leaqua.2013.11.003 · Cited by 584
A Survey on an Emerging Area: Deep Learning for Smart City Data
Chen, Q., Wang, W., Wu, F., De, S., Wang, R., Zhang, B., & Huang, X. (2019) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2019.2907718 · Cited by 167
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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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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