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|a 10.1109/TVCG.2016.2517641
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|a eng
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|a Liang, Yun
|e verfasserin
|4 aut
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| 245 |
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|a Objective Quality Prediction of Image Retargeting Algorithms
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| 264 |
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|c 2017
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|a Text
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|a Date Completed 13.08.2018
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|a Date Revised 13.08.2018
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Quality assessment of image retargeting results is useful when comparing different methods. However, performing the necessary user studies is a long, cumbersome process. In this paper, we propose a simple yet efficient objective quality assessment method based on five key factors: i) preservation of salient regions; ii) analysis of the influence of artifacts; iii) preservation of the global structure of the image; iv) compliance with well-established aesthetics rules; and v) preservation of symmetry. Experiments on the RetargetMe benchmark, as well as a comprehensive additional user study, demonstrate that our proposed objective quality assessment method outperforms other existing metrics, while correlating better with human judgements. This makes our metric a good predictor of subjective preference
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|a Journal Article
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|a Liu, Yong-Jin
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|a Gutierrez, Diego
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 23(2017), 2 vom: 02. Feb., Seite 1099-1110
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