Paper
4 March 2015 Saliency region and density maximization for salient object detection
Xin He, Huiyun Jing
Author Affiliations +
Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94430M (2015) https://doi.org/10.1117/12.2179942
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China
Abstract
In this paper, we propose an alternative salient object detection method based on maximum saliency region and density. The proposed approach can automatically detect the salient object with a well-defined boundary. Saliency region and density maximization is used as the quality function to find the optimal window containing a salient object. And for efficiently executing window search, a branch-and-bound search algorithm based on saliency region and density is proposed. Then the located window is used to initialize the GrabCut method, and the salient object with a well- defined boundary is extracted through applying GrabCut. Experimental results show that the proposed salient object detection approach outperforms the state-of-the-art methods.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xin He and Huiyun Jing "Saliency region and density maximization for salient object detection", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430M (4 March 2015); https://doi.org/10.1117/12.2179942
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KEYWORDS
Image segmentation

Visualization

Detection and tracking algorithms

Image retrieval

Object recognition

Binary data

Computer networks

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