The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Coarse-to-Fine Face Detection
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Cascaded detection is a commonly used technique that takes a coarse to fine detection philosophy: filter out most simple background windows using simple calculations, then process more difficult windows with complex ones.
“Cascaded detection is a commonly used technique [10, 125]. It takes a coarse to fine detection philosophy: to filter out most of the simple background windows using simple calculations, then to process those more difficult windows with complex ones.”
From Object Detection in 20 Years: A Survey (2023) · cites this paper as [125]
Citations
Cites
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Flagged first, then by citations
Research works printed but not linked: 5
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Cited by
Sorted by citations
Rapid object detection using a boosted cascade of simple features
Viola, P., & Jones, M. (2005) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 · doi:10.1109/cvpr.2001.990517 · Cited by 18,300
Robust Real-Time Face Detection
Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097
Object Detection in 20 Years: A Survey
Zou, Z., Chen, K., Shi, Z., Guo, Y., & Ye, J. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3238524 · Cited by 3,689
“Cascaded detection is a commonly used technique [10], [125].”
FloatBoost learning and statistical face detection
Li, S. Z., & Zhang, Z. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.68 · Cited by 525
Tu, Z. (2005) · Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 · doi:10.1109/iccv.2005.194 · Cited by 397
Grauman, K., & Leibe, B. (2011) · Synthesis Lectures on Artificial Intelligence and Machine Learning · doi:10.2200/s00332ed1v01y201103aim011 · Cited by 126
Bounding Part Scores for Rapid Detection with Deformable Part Models
Kokkinos, I. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33885-4_5 · Cited by 27
Metadata
- Authors
- Fleuret, F., & Geman, D.
- Affiliations
- University of Massachusetts Amherst (US)
- Venue
- International Journal of Computer Vision
- Published
- 2001-01
- Volume
- 41
- Issue
- 1-2
- Pages
- 85-107
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1601741105
- Cited by
- 273
- References
- 25
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 3 · 2022: 3 · 2021: 8 · 2020: 7 · 2019: 7 · 2018: 5 · 2017: 5 · 2016: 8 · 2015: 9 · 2014: 12 · 2013: 10 · 2012: 18
- FWCI
- 18.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Computer Vision (publishedVersion)
- Funders
- Multidisciplinary University Research Initiative
- Office of Naval Research
- Army Research Office
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Keywords
- face detection, coarse-to-fine detection, visual selection, sequential testing, false alarm rate, binary hypothesis testing, object representation
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