Automatic Image Cropping : A Computational Complexity Study

Jiansheng Chen, Gaocheng Bai, Shaoheng Liang, Zhengqin Li; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 507-515

Abstract


Attention based automatic image cropping aims at preserving the most visually important region in an image. A common task in this kind of method is to search for the smallest rectangle inside which the summed attention is maximized. We demonstrate that under appropriate formulations, this task can be achieved using efficient algorithms with low computational complexity. In a practically useful scenario where the aspect ratio of the cropping rectangle is given, the problem can be solved with a computational complexity linear to the number of image pixels. We also study the possibility of multiple rectangle cropping and a new model facilitating fully automated image cropping.

Related Material


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[bibtex]
@InProceedings{Chen_2016_CVPR,
author = {Chen, Jiansheng and Bai, Gaocheng and Liang, Shaoheng and Li, Zhengqin},
title = {Automatic Image Cropping : A Computational Complexity Study},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}