doi:10.1109/TVCG.2016.2517641engLiang, YunLiu, Yong LinGutierrez, DiegoObjective quality prediction of image retargeting algorithmsART-2017-97877Quality 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.2017http://zaguan.unizar.es/record/7967110.1109/TVCG.2016.2517641http://zaguan.unizar.es/record/79671oai:zaguan.unizar.es:79671IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 23, 2 (2017), 1099-1110All rights reservedhttp://www.europeana.eu/rights/rr-f/info:eu-repo/semantics/openAccess