Background Subtraction Approach Based on Independent Component Analysis
AbstractIn this work, a new approach to background subtraction based on independent component analysis is presented. This approach assumes that background and foreground information are mixed in a given sequence of images. Then, foreground and background components are identified, if their probability density functions are separable from a mixed space. Afterwards, the components estimation process consists in calculating an unmixed matrix. The estimation of an unmixed matrix is based on a fast ICA algorithm, which is estimated as a Newton-Raphson maximization approach. Next, the motion components are represented by the mid-significant eigenvalues from the unmixed matrix. Finally, the results show the approach capabilities to detect efficiently motion in outdoors and indoors scenarios. The results show that the approach is robust to luminance conditions changes at scene. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Jiménez-Hernández, H. Background Subtraction Approach Based on Independent Component Analysis. Sensors 2010, 10, 6092-6114.
Jiménez-Hernández H. Background Subtraction Approach Based on Independent Component Analysis. Sensors. 2010; 10(6):6092-6114.Chicago/Turabian Style
Jiménez-Hernández, Hugo. 2010. "Background Subtraction Approach Based on Independent Component Analysis." Sensors 10, no. 6: 6092-6114.