Point-cut: Fixation point-based image segmentation using random walk model
Xiaoliang Tian, Cheolkon Jung · 2015
When we see a scene, the visual saliency attracts our eyes at the first glance, and the human visual system (HVS) controls eye lens to focus on the salient object. Inspired by the HVS mechanism, we propose a fixation point-based image segmentation method using a random walk model, called Point-Cut. For a given image, we first adopt the visual saliency to find the regions that humans seldom or never fixate on, which are regard as background regions. Then, we segment the whole object regions where HVS focus the fixation using the superpixel based a random walk model. Experimental results show that the proposed method successfully segments foreground objects around the fixation point and achieves good performance even with the minimum user interaction comparable to state-of-the-art interactive image segmentation methods.