Title
A Hierarchical Approach To Robust Background Subtraction Using Color And Gradient Information
Abstract
We present a background subtraction method that uses multiple cues to detect objects robustly in adverse conditions. The algorithm consists of three distinct levels, i.e., pixel level, region level and frame level. At the pixel level, statistical models of gradients and color are separately used to classify each pixel as belonging to background or foreground. In the region level, foreground pixels obtained from the color based subtraction are grouped into regions and gradient based subtraction is then used to make inferences about the validity of these regions. Pixel based models are updated based on decisions made at the region level. Finally, frame level analysis is performed to detect global illumination changes. Our method provides the solution to some of the common problems that are not addressed by most background subtraction algorithms, such as fast illumination changes, repositioning of static background objects, and initialization of background model with moving objects present in the scene.
Publication Date
1-1-2002
Publication Title
Proceedings - Workshop on Motion and Video Computing, MOTION 2002
Number of Pages
22-27
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/MOTION.2002.1182209
Copyright Status
Unknown
Socpus ID
84964316524 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84964316524
STARS Citation
Javed, O.; Shafique, K.; and Shah, M., "A Hierarchical Approach To Robust Background Subtraction Using Color And Gradient Information" (2002). Scopus Export 2000s. 2674.
https://stars.library.ucf.edu/scopus2000/2674