A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2004 Papers
Combining Top-Down and Bottom-Up Segmentation
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 4 - Volume 04
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
Interactive product image search with complex scenes
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
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In this paper, we propose a novel automatic algorithm for foreground/background labeling. We aim to generate ROI cutout automatically for further processing such as image editing, classification and information retrieval. Different from traditional semi-supervised segmentation method, we use a rather weak prior on boundary label. Accordingly, a global cost function is proposed to combine our prior knowledge with pixel-level feature. We compute fuzzy matting components as building blocks to construct semantically meaningful mattes. Finally, these mattes are hierarchically clustered and ranked by central preference. Experimental results on a large benchmark data set demonstrate the performance of our algorithm.