Global Contrast based Salient Region Detection.
2011 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR).
(pp. 409 - 416).
Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their contents, and thus remains an important step in many computer vision tasks including image segmentation, object recognition, and adaptive compression. We propose a regional contrast based saliency extraction algorithm, which simultaneously evaluates global contrast differences and spatial coherence. The proposed algorithm is simple, efficient, and yields full resolution saliency maps. Our algorithm consistently outperformed existing saliency detection methods, yielding higher precision and better recall rates, when evaluated using one of the largest publicly available data sets. We also demonstrate how the extracted saliency map can be used to create high quality segmentation masks for subsequent image processing.
|Title:||Global Contrast based Salient Region Detection|
|Event:||IEEE Conference on Computer Vision and Pattern Recognition (CVPR)|
|Location:||Colorado Springs, CO|
|Dates:||2011-06-20 - 2011-06-25|
|Keywords:||SELECTIVE VISUAL-ATTENTION, IMAGE SEGMENTATION, EXTRACTION|
|UCL classification:||UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Engineering Science
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