Exploiting Surroundedness for Saliency Detection: A Boolean Map Approach

Jianming Zhang, Stan Sclaroff
2016 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Exploiting surroundedness for saliency detection: a boolean map approach This work was made openly accessible by BU Faculty. Please share how this access benefits you. Your story matters. Abstract A novel Boolean Map based Saliency (BMS) model is proposed. An image is characterized by a set of binary images, which are generated by randomly thresholding the image's color channels. Based on a Gestalt principle of figure-ground segregation, BMS computes saliency maps by analyzing the topological
more » ... ructure of Boolean maps. BMS is simple to implement and efficient to run. Despite its simplicity, BMS consistently achieves state-of-the-art performance compared with ten leading methods on five eye tracking datasets. Furthermore, BMS is also shown to be advantageous in salient object detection.
doi:10.1109/tpami.2015.2473844 pmid:26336114 fatcat:ra253jx625cuddlr4z7oakhjjm