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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiongkuo Min Guangtao Zhai Zhongpai Gao Ke Gu |
| Copyright Year | 2014 |
| Description | Author affiliation: Inst. of Image Commun. & Inf. Process., Shanghai Jiao Tong Univ., Shanghai, China (Xiongkuo Min; Guangtao Zhai; Zhongpai Gao; Ke Gu) |
| Abstract | Images usually contain areas that particularly attract people's attention and visual attention is an important feature of human visual system (HVS). Visual attention had been shown to be effective in improving performance of existing image quality assessment (IQA) metrics. However, with the quick advancement of IQA research, the booming of open IQA databases calls for associated comprehensive and accurate visual attention dataset. Despite of the large number of existing computational attention/saliency models, the most accurate measure of human attention is still human based. In this research, we first conduct extensive eye tracking experiments for all the pristine images from the seven widely used IQA databases (LIVE, TID2008, CSIQ, Toyama, LIVE Multiply Distortion, IVC and A57 databases). Then we propose a gaze-duration adaptive weighting approach to generate saliency maps from the eye tracking data. When applied on the IQA databases, experimental results suggest that accuracy of benchmark quality metrics, e.g. PSNR and SSIM can be systematically improved, outperforming existing saliency datasets. Both the eye tracking data and the saliency maps in this research will be made publicly available at gvsp.sjtu.edu.cn. |
| Sponsorship | IEEE Circuits Syst. Soc. |
| Starting Page | 894 |
| Ending Page | 897 |
| File Size | 2155095 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479934324 |
| DOI | 10.1109/ISCAS.2014.6865280 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-01 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Measurement Visualization Image quality PSNR Visual databases |
| Content Type | Text |
| Resource Type | Article |
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