A background model initialization algorithm for video surveillance

By Daniel Gutchess, M. Trajkovic, Eric Cohen-Solal, D. Lyons, Anil K. Jain. Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2001

296 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/2cbdeae4e91f3e4047c9ca1ff14eddea3fcfe18e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Thierry Bouwmans
2. Marc Van Droogenbroeck
3. Olivier Barnich
4. Sumaya H. Ahmed
5. Can Yang
6. Khaled M. El-Sayed
7. Xiaowei Zhou
8. Weichuan Yu

Citations in the corpus

• Statistical modeling of complex backgrounds for foreground object detection (2004, unknown): “Adjusting the learning rate based on the feedback from the optical flow could provide a possible solution [ 36 ].”
• ViBe: A Universal Background Subtraction Algorithm for Video Sequences (2011, methodology): “A method for properly initializing a Gaussian background model from a video sequence in which moving objects are present is proposed in [32].”
• Moving Object Detection by Detecting Contiguous Outliers in the Low-Rank Representation (2011, background): “An alternative mo tion-based approach is background estimation [11], [12].”
• Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art (2008, methodology): “According to Gutchess [113], several assumptions are necessary to make the task feasible.”