Co-Saliency Detection via Base Reconstruction
Xiaochun Cao, Yupeng Cheng, Zhiqiang Tao, Huazhu Fu · 2014
Co-saliency aims at detecting common saliency in a series of images, which is useful for a variety of multimedia applications. In this paper, we address the co-saliency detection to a reconstruction problem: the foreground could be well reconstructed by using the reconstruction bases, which are extracted from each image and have the similar appearances in the feature space. We firstly obtain a candidate set by measuring the saliency prior of each image. Relevance information among the multiple images is utilized to remove the inaccuracy reconstruction bases. Finally, with the updated reconstruction bases, we rebuild the images and provide the reconstruction error regarded as a negative correlational value in co-saliency measurement. The satisfactory quantitative and qualitative experimental results on two benchmark datasets demonstrate the efficiency and effectiveness of our method.