How the distribution of salient objects in images influences salient object detection

Abstract

We investigate the spatial distribution of salient objects in images. First, we empirically show that the centroid locations of salient objects correlate strongly with a centered, half-Gaussian model. This is an important insight, because it provides a justification for the integration of such a center bias in salient object detection algorithms. Second, we assess the influence of the center bias on salient object detection. Therefore, we integrate an explicit center bias into Cheng's state-of-the-art salient object detection algorithm. This way, first, we quantify the influence of the Gaussian center bias on salient object detection, second, improve the performance with respect to several established evaluation measures, and, third, derive a state-of-the-art unbiased salient object detection algorithm.