Co-saliency detection via similarity-based saliency propagation
Paper i proceeding, 2015

In this paper, we present a method for discovering the common salient objects from a set of images. We treat co-saliency detection as a pairwise saliency propagation problem, which utilizes the similarity between each pair of images to measure the common property with the guidance of a single saliency map image. Given the pairwise co-salient foreground maps, pairwise saliency is optimized by combining the initial background cues. Pairwise co-salient maps are then fused according to a novel fusion strategy based on the focus of human attention. Finally we adopt an integrated multi-scale scheme to obtain the pixel-level saliency map. Our proposed model makes the existing single saliency model perform well in co-saliency detection and is not overly sensitive to the initial saliency model selected. Extensive experiments on two benchmark databases show the superiority of our co-saliency model against the state-of-the-art methods both subjectively and objectively.

pairwise saliency propagation

optimization

Co-saliency detection

attention based fusion

Författare

Chenjie Ge

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Keren Fu

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Yijun Li

Jie Yang

Pengfei Shi

Li Bai

2015 IEEE International Conference on Image Processing (ICIP)

1845 - 1849

Ämneskategorier

Datorseende och robotik (autonoma system)