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Content Provider | IET Digital Library |
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Author | Niu, Yuzhen Lin, Wenqi Ke, Xiao Ke, Lingling |
Abstract | To overcome some major problems with traditional saliency evaluation metrics, full-reference image quality assessment (IQA) metrics, which have similar but stricter objectives, are used. Inspired by the root mean absolute error, the authors propose a fitting-based optimisation method for salient object detection algorithms. Their algorithm analyses the quantitative relationship between saliency and ground truth values, and uses the derived relationship to fit the saliency values to the original saliency maps. This ensures that the resulting images, which are composed of fitted values, are closer to the ground truth. The proposed algorithm first computes the statistics of the ground truth and saliency maps computed by each salient object detection algorithm. These statistics are used to compute the parameters of four fitting models, which generally agree with the characteristics of the statistical data. For a new saliency map, they use the fitting model with the computed parameters to obtain the fitted saliency values, which are confined to the range [0, 255]. Finally, they evaluate their saliency optimisation algorithm using traditional evaluation metrics, IQA metrics, and a content-based image retrieval application. The results show that the proposed approach improves the quality of the optimised saliency maps. |
Starting Page | 161 |
Ending Page | 172 |
Page Count | 12 |
ISSN | 17519632 |
Volume Number | 11 |
e-ISSN | 17519640 |
Issue Number | Issue 2, Mar (2017) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-cvi/11/2 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0027 |
Journal | IET Computer Vision |
Publisher Date | 2017-03-01 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Computer Vision And Image Processing Technique Content-based Image Retrieval Application Content-based Retrieval Fitting-based Optimisation Method Full-reference Image Quality Assessment Metrics Ground Truth Value Image Retrieval Image Visual Salient Object Detection Information Retrieval Technique IQA Metrics Object Detection Optical, Image And Video Signal Processing Optimisation Optimisation Technique Root Mean Absolute Error Saliency Maps Saliency Optimisation Algorithm Saliency Value Statistical Analysis Statistics Statistics Computation |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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