Automatic Image Cropping: A Computational Complexity Study

Jiansheng Chen, Gaocheng Bai, Shaoheng Liang, Zhengqin Li
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引用次数: 93

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.
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自动图像裁剪:计算复杂度研究
基于注意力的自动图像裁剪旨在保留图像中视觉上最重要的区域。在这种方法中,一个常见的任务是寻找最小的矩形,其中的注意力总和是最大的。我们证明,在适当的公式下,这项任务可以使用低计算复杂度的高效算法来实现。在一个实际有用的场景中,裁剪矩形的宽高比是给定的,这个问题可以用与图像像素数线性的计算复杂度来解决。我们还研究了多个矩形裁剪的可能性和一种实现全自动图像裁剪的新模型。
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