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Modelling visual saliency using degree centrality
- Source :
- IET Computer Vision. 4:218
- Publication Year :
- 2010
- Publisher :
- Institution of Engineering and Technology (IET), 2010.
-
Abstract
- Visual attention is an indispensable component of complex vision tasks. A multi-scale, complex network-based approach for determining visual saliency is described. It uses degree centrality (conceptually and computationally the simplest among all the centrality measures) over a network of image regions to form a saliency map. The regions used in the network are multiscale in nature with scale selected automatically. Experimental evaluation establishes the superiority of the method over existing saliency methods, even in noisy environments.
- Subjects :
- Computer science
business.industry
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Complex network
Machine learning
computer.software_genre
Image (mathematics)
Background noise
Computer Science::Computer Vision and Pattern Recognition
Component (UML)
Visual attention
Computer Vision and Pattern Recognition
Artificial intelligence
Scale (map)
business
Centrality
computer
Software
Visual saliency
Subjects
Details
- ISSN :
- 17519632
- Volume :
- 4
- Database :
- OpenAIRE
- Journal :
- IET Computer Vision
- Accession number :
- edsair.doi...........da9d07c9b91d80aa1fef656c6600233d