Traditional and recent approaches in background modeling for foreground detection: An overview T Bouwmans Computer Science Review 11, 31-66, 2014 | 835 | 2014 |
Background modeling using mixture of gaussians for foreground detection-a survey T Bouwmans, F El Baf, B Vachon | 717 | 2008 |
Robust PCA via Principal Component Pursuit: A review for a comparative evaluation in video surveillance T Bouwmans, EH Zahzah Computer Vision and Image Understanding 122, 22-34, 2014 | 547 | 2014 |
Recent advanced statistical background modeling for foreground detection-a systematic survey T Bouwmans Recent Patents on Computer Science 4 (3), 147-176, 2011 | 438 | 2011 |
Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset T Bouwmans, A Sobral, S Javed, SK Jung, EH Zahzah Computer Science Review 23, 1-71, 2017 | 394 | 2017 |
Deep neural network concepts for background subtraction: A systematic review and comparative evaluation T Bouwmans, S Javed, M Sultana, SK Jung Neural Networks 117, 8-66, 2019 | 388 | 2019 |
Robust subspace learning: Robust PCA, robust subspace tracking, and robust subspace recovery N Vaswani, T Bouwmans, S Javed, P Narayanamurthy IEEE signal processing magazine 35 (4), 32-55, 2018 | 351 | 2018 |
Background subtraction in real applications: Challenges, current models and future directions B Garcia-Garcia, T Bouwmans, AJR Silva Computer Science Review 35, 100204, 2020 | 311 | 2020 |
On the Applications of Robust PCA in Image and Video Processing T Bouwmans, S Javed, H Zhang, Z Lin, R Otazo Proceedings of the IEEE 106 (8), 1427-1457, 2018 | 270 | 2018 |
New trends on moving object detection in video images captured by a moving camera: A survey M Yazdi, T Bouwmans Computer Science Review 28, 157-177, 2018 | 245 | 2018 |
Statistical background modeling for foreground detection: A survey T Bouwmans, FE Baf, B Vachon Handbook of Pattern Recognition and Computer, 181-199, 2010 | 211 | 2010 |
Background Modeling and Foreground Detection for Video Surveillance T Bouwmans, F Porikli, B Höferlin, A Vacavant CRC Press, 2014 | 208 | 2014 |
Human Pose Estimation from Monocular Images: A Comprehensive Survey W Gong, X Zhang, J Gonzàlez, A Sobral, T Bouwmans, C Tu, E Zahzah Sensors 16 (12), 1966, 2016 | 189 | 2016 |
Type-2 fuzzy mixture of Gaussians model: application to background modeling F El Baf, T Bouwmans, B Vachon Advances in Visual Computing, 772-781, 2008 | 176 | 2008 |
Fuzzy integral for moving object detection F El Baf, T Bouwmans, B Vachon Fuzzy Systems, 2008. FUZZ-IEEE 2008.(IEEE World Congress on Computational …, 2008 | 173 | 2008 |
An extended center-symmetric local binary pattern for background modeling and subtraction in videos C Silva, T Bouwmans, C Frélicot International Joint Conference on Computer Vision, Imaging and Computer …, 2015 | 169 | 2015 |
Lrslibrary: Low-rank and sparse tools for background modeling and subtraction in videos A Sobral, T Bouwmans, E Zahzah Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and …, 2016 | 157 | 2016 |
On the role and the importance of features for background modeling and foreground detection T Bouwmans, C Silva, C Marghes, MS Zitouni, H Bhaskar, C Frelicot Computer Science Review 28, 26-91, 2018 | 151 | 2018 |
Subspace learning for background modeling: A survey T Bouwmans | 144 | 2009 |
Background–foreground modeling based on spatiotemporal sparse subspace clustering S Javed, A Mahmood, T Bouwmans, SK Jung IEEE Transactions on Image Processing 26 (12), 5840-5854, 2017 | 137 | 2017 |