Gaze-Based Object Segmentation

This letter addresses the problem of object segmentation with a gaze map and a group of candidate regions. First, we analyze distribution characteristics of gazes when people look at an image. Then, we summarize different cases of the group of candidate regions. Based on our analysis and summary, we develop three measures to evaluate the likelihood of a candidate region belonging to the target object and a pooling method to create a likelihood map of this object. Finally, the measures and pooling method are integrated with a proposed iterative strategy for generating the segmentation result. Experimental results demonstrate that our method can handle different types of gaze maps and different groups of candidate regions, and the overall performance of our method is better than that of the state-of-the-art method.