Geodesic Saliency Propagation for Image Salient Region Detection
Paper in proceedings, 2013

This paper proposes a novel geodesic saliency propagation method where detected salient objects may be isolated from both the background and other clutters by adding global considerations in the detection process. The method transmits saliency energy from a coarse saliency map to all image parts rather than from image boundaries in conventional cases. The coarse saliency map is computed using the combination of global contrast and Harris convex hull. Superpixels from pre-segmented image are used as pre-processing to further enhance the efficiency. The proposed propagation is geodesic distance assisted and retains the local connectivity of objects. It is capable of rendering a uniform saliency map while suppressing the background, leading to salient objects being popped out. Experiments were conducted on a benchmark dataset, visual comparisons and performance evaluations with eight existing methods have shown that the proposed method is robust and achieves the state-of-the-art performance.

Saliency map

Saliency detection

Geodesic distance

Saliency propagation


Keren Fu

Shanghai Jiao Tong University

Chen Gong

Shanghai Jiao Tong University

Irene Yu-Hua Gu

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Jie Yang

Shanghai Jiao Tong University

IEEE Int'l conf. on Image Processing (ICIP 2013), Sept.15-18, Melbourne, Australia


Areas of Advance


Life Science Engineering (2010-2018)

Subject Categories

Information Science

Signal Processing

Computer Vision and Robotics (Autonomous Systems)





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