Adaptive Background Filtering is a background reduction method that dynamically adjusts its filtering parameters based on temporal and spatial variations in the input data to distinguish foreground elements from a time-varying background more accurately than static filtering approaches.
163
Publications
13.2K
Citations
454
Authors
192
Institutions
Publications per year
2017–2026
37
Parents
Publications
163
Wallflower: principles and practice of background maintenance
Kentaro Toyama, John Krumm, Barry Brumitt et al. · 1999 · 1.7K citations
Improved Adaptive Gaussian Mixture Model for Background Subtraction
2004 · 1.7K citations
1–5 of 163
Authors
454
- DG
3
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- JZ
3
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- TB
3
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- TB
3
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- AP
3
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1–5 of 454
Institutions
192
Tsinghua University
Beijing, China
5 h-index
12 publications
723 citations
University of Ulsan
Ulsan, South Korea
3 h-index
9 publications
231 citations
Lehigh University
Bethlehem, United States
3 h-index
13 publications
1.5K citations
La Rochelle Université
La Rochelle, France
3 h-index
5 publications
515 citations
National University of Defense Technology
Changsha, China
3 h-index
8 publications
169 citations
University of Southern California
Los Angeles, United States
3 h-index
9 publications
1.1K citations
Kyushu University
Fukuoka, Japan
3 h-index
11 publications
459 citations
Athens Information Technology
Athens, Greece
3 h-index
7 publications
172 citations
1–8 of 192
Venues
- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
9 publications · 892 citations
9
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- Electronics Letters
3 publications · 259 citations
3
h-index
- Optical Engineering
3 publications · 89 citations
3
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- Journal of Visual Communication and Image Representation
3 publications · 44 citations
3
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- IEEE Transactions on Intelligent Transportation Systems
3 publications · 249 citations
3
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1–5