title: Objective Quality Prediction of Image Retargeting Algorithms.
abstract: 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.
authors.forename: Yun
authors.initials: Y
authors.lastname: Liang
authors.forename: Yong-Jin
authors.initials: YJ
authors.lastname: Liu
authors.forename: Diego
authors.initials: D
authors.lastname: Gutierrez