1 - Freely Moving Cameras (7 papers)
Y. Sheikh, O. Javed, T. Kanade, “Background Subtraction for Freely Moving Cameras”, IEEE International Conference on Computer Vision, ICCV 2009, pages 1219-1225, September 2009.
Y. Wu, X. He, T. Nguyen, “Moving Objects Detection with Freely Moving Camera via Background Motion Subtraction”, IEEE Transactions on Circuits and Systems for Video Technology, November 2015.
Y. Jin, L. Tao, H. Di, N. Rao, G. Xu, "Background Modeling from a Free-Moving Camera by Multi-Layer Homography Algorithm", IEEE International Conference on Image Processing, ICIP 2008, 2008.
T. Minematsu, A. Shimada, H. Uchiyama, V. Charvillat, R. Taniguchi, “Reconstruction-Based Change Detection with Image Completion for a Free-Moving Camera”, MDPI Sensors, 2018.
D. Sugimura, F. Teshima, T. Hamamoto, "Online Background Subtraction with Freely Moving Cameras using Different Motion Boundaries", Image and Vision Computing, June 2018.
C. Zhao, A. Sain, Y. Qu, Y. Ge, H. Hu, "Background Subtraction based on Integration of Alternative Cues in Freely Moving Camera", IEEE Transactions on Circuits and Systems for Video Technology, 2018.
H. Sajid, S .Cheung, N.Jacob, "Motion and appearance based background subtraction for freely moving cameras", Signal Processing: Image Communication, Volume 75, pages 11-21, July 2019.
C. Zhao, A. Sain, Y. Qu, Y. Ge, H. Hu, "Background Subtraction Based on Integration of Alternative Cues in Freely Moving Camera", IEEE Transactions on Circuits and Systems for Video Technology, Volume 29, No. 7, pages 1933-1945, July 2019.
2 - Online Moving Cameras (2 papers)
A. Elqursh, A. Elgammal, “Online Moving Camera Background Subtraction”, European Conference on Computer Vision, ECCV 2012, pages 228-241, 2012.
Y. Zhu, A. Elgammal, "A Multilayer-Based Framework for Online Background Subtraction with Freely Moving Cameras", Preprint, September 2017.
3 - Moving Cameras (30 papers)
M. Unger, M. Asbach, P. Hosten, “Enhanced background subtraction using global motion compensation and mosaicing”, International Conference on Image Processing, ICIP 2008, pages 2708-2711, October 2008.
Y. Sugaya K. Kanata, “Extracting Moving Objects from a Moving Camera Video Sequence”, Symposium on Sensing via Image Information, SSII 2004, pages 279–284, Yokohama, Japan, June 2004.
N. Mishra, M. Bhuyan, T. Malathi, Y. Iwahori, R. Woodham, “Pixel-wise background segmentation with moving camera”, International Conference on Pattern Recognition and Machine Intelligence, PReMI 2013, pages 423-429, Kolkata; India; December 2013.
F. Setyawan, J. Tan, H. Kim, S. Ishikawa, “Detection of Moving Objects in a Video Captured by a Moving Camera using Error Reduction”, SICE Annual Conference 2014, pages 347-352, Sapporo, Japan, September 2014.
T. Minematsu, H. Uchiyama, A. Shimada, H. Nagahara, R. Taniguchi, “Evaluation of foreground detection methodology for a moving camera”, Korea-Japan Joint Workshop on Frontiers of Computer Vision, FCV 2015, January 2015.
C. Cuevas, R. Mohedano, N. Garcia, "Statistical moving object detection for mobile devices with camera", IEEE International Conference on Consumer Electronics, ICCE 2015, pages 15-16, January 2015.
H. Bhakar, K. Dwivedi, D. Dogra, M. Al-Mualla, L. Mihaylova, “Autonomous detection and tracking under illumination changes, occlusions and moving camera”, Signal Processing, June 2015.
F. Sun, K. Qin, W. Sun, H. Guo, “Fast background subtraction for moving cameras based on nonparametric models”, Journal of Electronic Imaging. May 2016.
H. Sajid, S Cheung, “Background Subtraction for Static and Moving Camera”, IEEE International Conference on Image Processing, ICIP 2015, 2015.
H. Sajid, "Robust Background Subtraction for Moving Cameras and Their Applications in Ego-Vision Systems", PhD Thesis, University of Kentucky, USA, 2016.
D. Zamalieva, A. Yilmaz, “Background Subtraction for the Moving Camera: A Geometric Approach”, Computer Vision and Image Understanding, Volume 127, pages 73-85, October 2014.
D. Zamalieva, A. Yilmaz, J. Davis, “A Multi-Transformational Model for Background Subtraction with Moving Cameras”, European Conference on Computer Vision, ECCV 2014, 2014
D. Zamalieva, A. Yilmaz, J. Davis, “Exploiting Temporal Geometry for Moving Camera Background Subtraction”, International Conference on Pattern Recognition, ICPR 2014, 2014.
D. Zamalieva, “Transformational Models for Background Subtraction with Moving Cameras”, PhD thesis, The Ohio State University, 2014.
T. Kryjak, M. Komorkiewicz, M. Gorgon, "Real-time Implementation of Foreground Object Detection From a Moving Camera Using the ViBe Algorithm", Computer Science and Information System, Volume 11, No. 4, pages 1617-1637, October 2014.
T. Minematsu, H. Uchiyama, A. Shimada, H. Nagahara, R. Taniguchi, "Adaptive background model registration for moving camera", Pattern Recognition Letters, 2017.
M. Nakahata, L. Thomaz, A. da Silva, E.da Silva, S. Netto, "Anomaly detection with a moving camera using spatio-temporal codebooks", Multidimensional Systems and Signal Processing, pages 1-30, March 2017.
L. Gong, M. Yu, T. Gordon, "Online codebook modeling based background subtraction with a moving camera", International Conference on Frontiers of Signal Processing, ICFSP 2017, pages136-140, 2017.
Y. Zhou, S. Maskell, “Moving object detection using background subtraction for a moving camera with pronounced parallax”, Sensor Data Fusion: Trends, Solutions, Applications, October 2017.
K. Makino, T. Shibata, S. Yachida, T. Ogawa, K. Takahashi, “Moving-object detection method for moving cameras by merging background subtraction and optical flow methods”, IEEE GlobalSIP 2017, Montreal, Canada, 2017.
S. Diamantas, K. Alexis, "Optical Flow Based Background Subtraction with a Moving Camera: Application to Autonomous Driving", Preprint, 2018.
B. Afonso, L. Cinelli, L. Thomaz, A. da Silva, E. da Silva, S. Netto, “Moving-Camera Video Surveillance in Cluttered Environments using Deep Features”, IEEE International Conference on Image Processing, ICIP 2018, pages 2296-2300, Athens, Greece, 2018.
L. Thomaz, E. Jardim, A. da Silva, E. da Silva, S. Netto , H. Krim, "Anomaly Detection in Moving-Camera Video Sequences using Principal Subspace Analysis", IEEE Transactions on Circuits and Systems I: Regular Papers, 2017.
C. Gao, B. Moore, R. Nadakuditi, “Augmented robust PCA for foreground-background separation on noisy, moving camera video”, Preprint, September 2017.
B. Moore, C. Gao, R. Nadakuditi , “Panoramic robust PCA for foreground-background separation on noisy, free-motion camera video”, Preprint, December 2017.
B. Moore, "Robust Algorithms for Low-Rank and Sparse Matrix Models", PhD Thesis, University of Michigan, June 2018.
Y. Yu, L. Kurnianggoro, K. Jo,"Moving Object Detection for a Moving Camera Based on Global Motion Compensation and Adaptive Background Model", International Journal of Control, Automation and Systems, Volume 17, pages 1-9, 2019.
J. Wei, J. Jiang, A. Yilmaz, "MBS-Net a Moving-Camera Background Subtraction Network for Autonomous Driving", ISPRS-International Archives of the Photogrammetry, 2021.
I. Delibasoglu, I. Kosesoy, M. Kotana, F. Selameta, "Motion Detection in Moving Camera Videos using Background Modelling and Flownet", Journal of Visual Communication and Image Representation, September 2022.
4 - Hand-held Cameras (1 paper)
R. Hamid, A. Sarma, D. Decoste, N. Sundaresan, “Fast Approximate Matching of Cell-Phone Videos for Robust Background Subtraction”, Preprint, 2014.
5 - Mobile Cameras (2 papers)
P. Boluk, K. Akkaya, “Performance evaluation of background subtraction algorithms for Android devices deployed in Wireless Multimedia Sensor Networks”, International Wireless Communications and Mobile Computing Conference, IWCMC 2014, pages 779-784, August. 2014.
K. Yi, K. Yun, S. Kim, H. Chang, H. Jeong, J. Choi, "Detection of Moving Objects with Non-Stationary Cameras in 5.8ms: Bringing Motion Detection to your Mobile Device", IEEE International Conference on Computer Vision and Pattern Recognition, CVPR 2013, 2013.
6 - UAV Cameras (1 paper)
G. Tzanidou, P. Perez, G. Hummel, M. Schmitt, P. Stutz, D. Monekosso, P. Remagnino, “Telemetry assisted frame registration and background subtraction in low-altitude UAV videos”, IEEE International Conference on in Advanced Video and Signal Based Surveillance, AVSS 2015, pages 1-6, 2015.
7 - PTZ Cameras (17 papers)
A. Ferone, L. Maddalena, “Neural Background Subtraction for Pan-Tilt-Zoom Cameras”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, September 2013.
C. Guillot, M. Taron, P. Sayd, Q. Pham, C. Tilmant, J. Lavest, “Background Subtraction for PTZ Cameras Performing a Guard Tour and Application to Cameras with Very Low Frame Rate”, ACCV 2010 Workshops, pages 33-42, 2010.
P. Azzari, L. Di Stefano, A. Bevilacqua, “An effective real-time mosaicing algorithm apt to detect motion through background subtraction using a PTZ camera”, IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2005, pages 511-516, September 2005.
Z. Cui, A. Li, K. Jiang, “Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration”, Journal of Multimedia , Volume 9, No. 3, pages 363-370, March 2014.
N. Liu, H. Wu, L. Lin, “Hierarchical Ensemble of Background Models for PTZ-based Video Surveillance”, IEEE Transactions on Cybernetics, 2014.
A. Yildirim, A. Alkar, K. Ince, “Background modelling for pan tilt camera”, Signal Processing and Communications Applications Conference, SIU 2014, pages 1191-1194, April 2014.
O. Ivanov, “Adaptation of Known Background Subtraction Methods in the Case of a Moving PTZ Camera Mounted on a Mobile Platform”, Pattern Recognition and Image Analysis, Volume 24, No. 2, page 318–323, 2014.
H. Sajid, S. Cheung, N. Jacobs, “Appearance based background subtraction for PTZ cameras”, Signal Processing: Image Communication, Volume 47, pages 417-425, September 2016.
M. Karlsson, “Evaluation of Background Subtraction in Pan-Tilt Camera Tracking”, Master Thesis, Chalmers University, Sweden, 2016.
D. Avola, L. Cinque, G. Foresti, C. Massaroni, D. Pannone, "A keypoint-based method for background modeling and foreground detection using a PTZ camera", Pattern Recognition Letters, 2016.
D. Avola, M. Bernardini, L. Cinque, G. Foresti, C. Massaroni, "Combining Keypoint Clustering and Neural Background Subtraction for Real-time Moving Object Detection by PTZ Cameras", International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018, pages 638-645, 2018.
D. Avola, M. Bernardi, L. Cinque, C. Massaroni, "Fusing Self-Organized Neural Network and Keypoint Clustering for Localized Real-Time Background Subtraction", International Journal of Neural Systems, 2020.
A. Zheng, L. Zhang, W. Zhang, C. Li, J. Tang, B. Luo, "Local-to-global background modeling for moving object detection from non-static cameras", Multimedia Tools and Applications, pages 1-17, July 2016.
L. Esteberena, R. Barbuzza, J. D’Amato, A. Perez, L. Dominguez, A. Rubiales, "Adaptation of Background Subtraction Algorithms for PTZ Cameras", SLGRVPI 2017, 2017.
E. Komagal, B. Yogameena, “Region MoG and texture descriptor-based motion segmentation under sudden illumination in continuous pan and excess zoom”, Multimedia Tools and Applications, 2017.
E. Komagal, B. Yogameena, "Foreground segmentation with PTZ camera: a survey", Multimedia Tools and Applications, pages 1-54, 2018.
G. Allebosch, D. Van Hamme, P. Veelaert, W. Philips, "Robust Pan/Tilt Compensation for Foreground–Background Segmentation", MDPI Sensors, 2019.