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Keyword

background modeling

Description: Background modeling is a computer-vision technique for representing a scene’s static content to distinguish moving objects from the background.
OpenAlex ID: keywords/background-modeling
The Rietveld method
1993 · R. A. Young · Crystal Research and Technology · 2,566
ViBe: A Universal Background Subtraction Algorithm for Video Sequences
2010 · O Barnich, M Van Droogenbroeck · IEEE Transactions on Image Processing · 1,888
Image change detection algorithms: a systematic survey
2005 · R.J. Radke, S. Andra, et al. · IEEE Transactions on Image Processing · 1,870
Background and foreground modeling using nonparametric kernel density estimation for visual surveillance
2002 · A. Elgammal, R. Duraiswami, et al. · Proceedings of the IEEE · 1,510
Real-time foreground–background segmentation using codebook model
2005 · Kyungnam Kim, Thanarat H. Chalidabhongse, et al. · Real-Time Imaging · 1,422
Learning Background-Aware Correlation Filters for Visual Tracking
2017 · Hamed Kiani Galoogahi, Ashton Fagg, et al. · IEEE International Conference on Computer Vision (ICCV) · 1,265
A texture-based method for modeling the background and detecting moving objects
2006 · M. Heikkila, M. Pietikainen · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1,249
Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm
2019 · Canyi Lu, Jiashi Feng, et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1,146
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Geodesic active contours and level sets for the detection and tracking of moving objects
2000 · N. Paragios, R. Deriche · IEEE Transactions on Pattern Analysis and Machine Intelligence · 999
On-line Boosting and Vision
2006 · H. Grabner, H. Bischof · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 997
Statistical Modeling of Complex Backgrounds for Foreground Object Detection
2004 · L. Li, W. Huang, et al. · IEEE Transactions on Image Processing · 991
The LHCb Simulation Application, Gauss: Design, Evolution and Experience
2011 · M Clemencic, G Corti, et al. · Journal of Physics Conference Series · 990
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Collaborative Representation for Hyperspectral Anomaly Detection
2014 · Wei Li, Qian Du · IEEE Transactions on Geoscience and Remote Sensing · 752
More About Metaphor
1977 · Max Black · dialectica · 734
A unified approach to salient object detection via low rank matrix recovery
2012 · Xiaohui Shen, Ying Wu · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 700
Traditional and recent approaches in background modeling for foreground detection: An overview
2014 · Thierry Bouwmans · Computer Science Review · 676
A comprehensive review of background subtraction algorithms evaluated with synthetic and real videos
2014 · Andrews Sobral, Antoine Vacavant · Computer Vision and Image Understanding · 654
Bayesian modeling of dynamic scenes for object detection
2005 · Y. Sheikh, M. Shah · IEEE Transactions on Pattern Analysis and Machine Intelligence · 638
Calibration of the Rossi X‐Ray Timing Explorer Proportional Counter Array
2006 · Keith Jahoda, Craig B. Markwardt, et al. · The Astrophysical Journal Supplement Series · 599
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Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation
2015 · Yang Xu, Zebin Wu, et al. · IEEE Transactions on Geoscience and Remote Sensing · 596
Motion-based background subtraction using adaptive kernel density estimation
2004 · A. Mittal, N. Paragios · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 591
Background segmentation with feedback: The Pixel-Based Adaptive Segmenter
2012 · Martin Hofmann, Philipp Tiefenbacher, et al. · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · 583
Saliency detection via Cellular Automata
2015 · Yao Qin, Huchuan Lu, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 494
OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes
2013 · David Tamborero, Abel Gonzalez-Perez, et al. · Bioinformatics · 489
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A Low-Rank and Sparse Matrix Decomposition-Based Mahalanobis Distance Method for Hyperspectral Anomaly Detection
2015 · Yuxiang Zhang, Bo Du, et al. · IEEE Transactions on Geoscience and Remote Sensing · 485
Works count: 5,069
Citation count: 80,780
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