Temporal statistics can be computed to generate a background image as follows:
1. mean - median - histogram mode (17 papers)
Whole bootstrap sequence (13 papers)
R. Collins, A. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, O. Hasegawa, “A System for Video Surveillance and Monitoring”, Technical Report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, May 2000.
I. Haritaoglu, D. Harwood, L. Davis, “W4: Real-Time Surveillance of People and Their Activities”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 22, No. 8, pages 809-830, August 2000.
M. Molinier, T. Häme, H. Ahola, “3D Connected Components Analysis for Traffic Monitoring in Image Sequences Acquired from a Helicopter”, Scandinavian Conference, SCIA 2005, page 141, Joensuu, Finland, June 2005.
Y. Liu, H. Yao, W. Gao, X. Chen, D. Zhao, “Nonparametric Background Generation”, International Conference on Pattern Recognition, ICPR 2006, Volume 4, pages 916-919, 2006.
Y. Liu, H. Yao, W. Gao, X. Chen, D. Zhao, “Nonparametric Background Generation”, Journal of Visual Communication and Image Representation, Volume 18, pages 253-263, 2007.
S. Amri, W. Barhoumi, E. Zagrouba, "Unsupervised Background Reconstruction based on iterative Median Blending and Spatial Segmentation", IEEE International Conference on Imaging, Systems and Techniques, pages 411-416, 2010.
Y. Chung, J. Wang, S. Cheng, “Progressive Background Image Generation”, IPPR Conference on Computer Vision, Graphics and Image Processing, CVGIP 2002, pages 858-865, 2002.
J. Wang, S. Cheng, “Progressive Background Image Generation”, Journal of National Taiwan University, Volume 47, No. 2 , 2002.
R. Mora Colque, G. Camara-Chavez, “Progressive Background Image Generation of Surveillance Traffic Videos Based on a Temporal Histogram Ruled by a Reward/Penalty Function”, SIBGRAPI 2011, 2011.
S. Cho, H. Kang, J. Yoo, "Background Generation using Mean-shift and Fast Marching Method", International Conference on Computer Science and its Applications, pages 1-6, December 2009.
S. Cho, H. Kang, "A New Background Generation Method based on MRF framework", International Conference on Computing, Communications and Control Technologies, March 2011.
J. Villalba-Espinosa, J. Gonzalez-Linares, J. Cozar, N. Guil, “Pixel-based Background Initialization using Spatio-Temporal Restrictions”, Knowledge-Based and Intelligent Information and Engineering Systems, 2012.
H. Kaur, M. Kaur, S. Kaur, M. Rashid, "Background Extraction using a Temporal Fractional Derivative", International Conference on Latest Trends in Engineering and Technology, ICLTET 2023, Mohali, India, July 2023.
Randomly selected frames (4 papers)
K. Teknomo, P. Fernandez, “Background Image Generation using Boolean Operations”, Philippine Computing Journal, Volume 4, Issue 2, pages 43-49, 2009.
P. Abu, V. Chu, P. Fernandez, "A Monte-Carlo-based algorithm for background generation",Philippine Information and Communications Technology Journal, Volume 6, pages 4-10, 2013.
P. Abu, P. Fernandez, “Extendibility of the Teknomo-Fernandez Algorithm for Background Image Generation”, ACACOS 2013, 2013.
P. Abu, P. Fernandez, “Extending the Teknomo-Fernandez Background Image Generation Algorithm on the HSV Colour Space”, WSEAS Transactions on Information Science and Applications, November 2015.
2. Mixture of Gaussians (4 papers)
C. Stauffer, W. Grimson, “Adaptive background mixture models for real-time tracking”, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 1999, pages 246-252, 1999.
M. Cristani, M. Bicego, V. Murino, “Multi-Level Background Initialization using Hidden Markov Models”, ACM SIGMM Workshop on Video Surveillance, IWVS 2003, pages 11-19, 2003.
Z. Sheng, X. Cui, “An adaptive learning rate GMM for background extraction”, International Conference on Computer Science and Software Engineering, pages 174-176, December 2008.
B. Qin, J. Wang, J. Gao, T. Pang, F. Su, "A Traffic Video Background Extraction Algorithm Based on Image Content Sensitivity", International Conference on Swarm Intelligence, ICSI 2010, pages 603-610, 2010.
3. Kernel Density Estimation (1 paper)
A. Elgammal, D. Harwood, L. Davis, “Non-parametric Model for Background Subtraction”, European Conference on Computer Vision, ECCV 2000, pages 751-767, Dublin, Ireland, June 2000.
4. Selected Frames (1 paper)
A. Djerida, Z. Zhao, J. Zhao, "Robust background generation based on an effective frames selection method and an efficient background estimation procedure (FSBE)", Signal Processing: Image Communication, 2019.
5. Co-occurrence Spatial–Temporal Model (1 paper)
W. Zhou, Y Deng, B. Peng, S. Xiang, S. Kaneko, “Co-occurrence spatial–temporal model for adaptive background initialization in high-dynamic complex scenes”, Signal Processing: Image Communication, Volume 11, 2023.