Where´s waldo? human figure segmentation using saliency maps

Human figure segmentation (HFS) is at the very core of many image and video processing tasks. Many solutions have been proposed for the separation of objects, or more specifically human figures, from image background in a video scene. Unfortunately, these solutions do not provide tight human segmentation in the most general conditions, so only a coarse segmentation of human figures can be assumed. In this paper it is assumed that a rectangular, not necessarily tight, segmentation of a human figure is available and a way to refine this segmentation is proposed. We use saliency detection for HFS in a single image, thus creating a mask that eliminates most of the background in the rectangular input while maintaining the human figure mostly intact. The proposed technique is a generalization over recently proposed saliency detection methods in order to better accommodate the special conditions of this specific problem. Tests show that saliency detection is beneficial for HFS. In addition, the proposed saliency detection is shown to improve HFS results and presents a viable solution for HFS in a single image or a video stream.