Title
Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement.
Abstract
•Gestalt laws guided saliency detection via characterizing HVS and forming objects.•Smooth at superpixel and object levels by fusing bottom-up and top-down mechanisms;•Background suppression with background correlation term & spatial compactness term.•Two-stage refinement to show best among 10 state-of-the-art methods on 5 datasets.
Year
DOI
Venue
2018
10.1016/j.patcog.2018.02.004
Pattern Recognition
Keywords
Field
DocType
Background connectivity,Gestalt laws guided optimization,Image saliency detection,Feature fusion,Human vision perception
Pattern recognition,Visual cortex,Salience (neuroscience),Precision and recall,Figure–ground,Gestalt psychology,Artificial intelligence,Cognition,Fuse (electrical),Perception,Mathematics
Journal
Volume
Issue
ISSN
79
1
0031-3203
Citations 
PageRank 
References 
32
1.10
38
Authors
8
Name
Order
Citations
PageRank
Yijun Yan1342.85
Jinchang Ren2114488.54
Genyun Sun314917.27
Huimin Zhao420623.43
Junwei Han53501194.57
Xuelong Li615049617.31
Stephen Marshall7353.22
Jin Zhan8393.57