Foreground Detection Using the Choquet Integral

Abstract

Foreground Detection is a key step in background subtraction problem. This approach consists in the detection of moving objects from static cameras through a classification process of pixels as foreground or background. The presence of some critical situations i.e noise, illumination changes and structural background changes produces an uncertainty in the classification of image pixels which can generate false detections. In this context, we propose a fuzzy approach using the Choquet integral to avoid the uncertainty in the classification. The experiments on different video datasets have been realized by testing different color space and by fusing color and texture features. The proposed method is characterized through robustness against illumination changes, shadows and little background changes, and it is validated with the experimental results.