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Global contrast based salient region detection

2011· article· en· 3,095 citations· W2037954058 on OpenAlex· 10.1109/cvpr.2011.5995344

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Abstract

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information.

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The record

Venue
Topic
Visual Attention and Saliency Detection
Field
Computer Science
Canadian institutions
Kootenay Association for Science & Technology
Funders
National Key Research and Development Program of ChinaNational High-tech Research and Development ProgramEngineering and Physical Sciences Research CouncilNational Natural Science Foundation of China
Keywords
Contrast (vision)SalientComputer scienceArtificial intelligence
Has abstract in OpenAlex
yes