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How saliency maps can be used to create high quality cropping of images
Grado:
How saliency maps can be used to create high quality cropping of images
Abstract The work is about a method for cropping photographs given minimal information about the location of important content, provided by visual attention. The system should use visual saliency data such as [1] (or any of the effective and recent methods cited in [2]) to identify important content and compute the best crop for any given aspect ratio or size, enabling applications such as automatic snapshot recomposition, adaptive documents, and thumbnailing. A proposal for cropping is given in [3] for in a general optimization framework that facilitates adding new composition rules, as well as adapting the system to particular applications.
References:
[1] Ming-Ming Cheng, Guo-Xin Zhang, Niloy J. Mitra, Xiaolei Huang, Shi-Min Hu, Global Contrast based Salient Region Detection, IEEE CVPR, 2011, p. 409-416 (http://mmcheng.net/mftp/SalObj/ChengSaliencyCVPR2011.pdf).
[2] http://mmcheng.net/salobj/
[3] Anthony Santella, Maneesh Agrawala, Doug DeCarlo, David Salesin, and Michael Cohen. 2006. Gaze-based interaction for semi-automatic photo cropping. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '06), Rebecca Grinter, Thomas Rodden, Paul Aoki, Ed Cutrell, Robin Jeffries, and Gary Olson (Eds.). ACM, New York, NY, USA, 771-780. DOI=10.1145/1124772.1124886 http://doi.acm.org/10.1145/1124772.1124886