协同视觉显著性检测方法综述

Co-saliency detection is a new branch with the rapid development in the field of visual attention, which concerns the detection of the common salient objects from multiple relevant scene images, and can be widely used in various computer vision tasks. Considering the key point of current research is the design of feature extraction strategy, the existing co-saliency detection methods are firstly summarized and qualitatively analyzed according to the different feature extraction strategies in this paper. Subsequently, based on the subjective and quantitative comparisons in the five open datasets, the performance of the state-of-the-art algorithms is evaluated, the influence of the feature extraction strategy on the performance of algorithms and the complexity of the datasets is analyzed, and the difference of co-saliency detection and saliency detection is also verified. Finally, the conclusion of this paper are presented, the problems of current research and the future development are also discussed.