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In this paper, we first propose a novel no-reference (NR) image quality assessment (IQA) method for retargeted image based on the rank learning approach. Firstly, image features for each retargeted image are extracted, which should not only represent the image characteristics but also be sensitive to the retargeted distortions. Specifically, the image feature should be able to capture the shape distortions,...
Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image...
In image processing, cartoon character classification, retrieval, and synthesis are critical, so that cartoonists can effectively and efficiently make cartoons by reusing existing cartoon data. To successfully achieve these tasks, it is essential to extract visual features that comprehensively represent cartoon characters and to construct an accurate distance metric to precisely measure the dissimilarities...
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