Conference Proceedings
Probabilistic hypergraph optimization for salient object detection
J Zhang, S Fang, KA Ehinger, W Guo, W Yang, H Wei
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics | Published : 2017
Abstract
In recent years, many graph-based methods have been introduced to detect saliency. These methods represent image regions and their similarity as vertices and edges in a graph. However, since they only represent pairwise relations between vertices, they give an incomplete representation of the relationships between regions. In this work, we propose a hypergraph based optimization framework for salient object detection to include not only the pairwise but also the higher-order relations among two or more vertices. In this framework, besides the relations among vertices, both the foreground and the background queries are explicitly exploited to uniformly highlight the salient objects and suppre..
View full abstractGrants
Awarded by National Natural Science Foundation of China