Abstract
Many people fail to take exquisite pictures in a beautiful scenery for the lack of professional photography knowledge. In this paper, we focus on how to aid people to master daily life photography using a computational layout recommendation method. Given a selected scene, we first generate several synthetic photos with different layouts using 3D estimation. Then we employ a 3D layout aesthetic estimation model to rank the proposed photos. The results with high scores are selected as layout recommendations, which is then translated to a hint for where people shall locate. The key to our success lies on the combination of 3D structures with aesthetic models. The subjective evaluation shows superior preference of our method to previous work. We also give a few application examples to show the power of our method in creating better daily life photographs.
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Acknowledgments
This work is supported by National Science Foundation of China (61321491, 61202320), Research Project of Excellent State Key Laboratory (61223003), Research Fund of the State Key Laboratory for Novel Software Technology at Nanjing University (ZZKT2016B09), and Collaborative Innovation Center of Novel Software Technology and Industrialization.
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Zhang, B., Ju, R., Ren, T., Wu, G. (2016). Say Cheese: Personal Photography Layout Recommendation Using 3D Aesthetics Estimation. In: Chen, E., Gong, Y., Tie, Y. (eds) Advances in Multimedia Information Processing - PCM 2016. PCM 2016. Lecture Notes in Computer Science(), vol 9917. Springer, Cham. https://doi.org/10.1007/978-3-319-48896-7_2
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DOI: https://doi.org/10.1007/978-3-319-48896-7_2
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