A Simple and efficient saliency detector for background subtraction

In this paper we present a simple and computationally efficient method for detecting visually salient areas. The proposed method is based on searching image segments whose intensity values are more accurately described by the intensity distribution of the object compared to the distribution of the surrounding area. The practical implementation applies a sliding window approach, where the distributions of the objects and surroundings are estimated using semi-local intensity histograms that are efficiently evaluated using integral histogram approach. The introduced approach requires no training and no additional segmentation algorithms. Saliency detection can be used in background subtraction and we show that the proposed method is especially effective in the case where the scene is highly dynamic or the camera is not still. Furthermore using our approach we are able to detect also targets that are not moving. Comparisons with state-of-the-art saliency detectors and background subtraction techniques indicate that the introduced approach results in high performance and accuracy, outperforming the reference methods.