NDLI: CF-based optimisation for saliency detection

Content Provider	IET Digital Library
Author	Niu, Yuzhen Lin, Wenqi Ke, Xiao
Abstract	In view of the observation that saliency maps generated by saliency detection algorithms usually show similarity imperfection against the ground truth, the authors propose an optimisation algorithm based on clustering and fitting (CF) for saliency detection. The algorithm uses a fitting model to represent the quantitative relationship between ground truth and algorithm-generated saliency maps. The authors use the K-means method to cluster the images into k clusters according to the similarities among images. Image similarity is measured in terms of scene and colour by using the GIST and colour histogram features, after which the fitting model for each cluster is calculated. The saliency map of a new image is optimised by using one of the fitting models which correspond to the cluster to which the image belongs. Experimental results show that their CF-based optimisation algorithm improves the performance of various single image saliency detection algorithms. Moreover, the improvement achieved by their algorithm when using both CF strategies is greater than the improvement achieved by the same algorithm when not using the clustering strategy. In addition, their proposed optimisation algorithm can also effectively optimise co-saliency detection algorithms which already consider multiple similar images simultaneously to improve saliency of single images.
Starting Page	365
Ending Page	376
Page Count	12
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 4, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0512
Journal	IET Computer Vision
Publisher Date	2018-01-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	CF-based Optimisation Clustering And Fitting Colour Histogram Features Computer Vision And Image Processing Technique GIST Image Colour Analysis Image Enhancement Image Saliency Detection Algorithm Image Similarity K-means Method Optical, Image And Video Signal Processing Optimisation Optimisation Technique Saliency Maps
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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