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Background Subtraction Approach Based on Independent Component Analysis
Centro de Investigación en Ciencia Aplicada y Tecnología Aplicada Cerro Blanco No. 141. Col. Colinas del Cimatario, Santiago de Querétaro, Querétaro, Mexico
Received: 26 April 2010; in revised form: 16 May 2010 / Accepted: 28 May 2010 / Published: 18 June 2010
Abstract: In 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.
Keywords: background subtraction; independent component analysis; motion detection
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Cite This Article
MDPI and ACS Style
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.
Jiménez-Hernández, Hugo. 2010. "Background Subtraction Approach Based on Independent Component Analysis." Sensors 10, no. 6: 6092-6114.