Image cropping is essential in image editing for obtaining a compositionally enhanced image. In display media, image cropping is a prospective technique for automatically creating media content. However, image cropping for media contents is often required to satisfy various constraints, such as an aspect ratio and blank regions for placing texts or objects. We call this problem image cropping under design constraints. To achieve image cropping under design constraints, we propose a score function-based approach, which computes scores for cropped results whether aesthetically plausible and satisfies design constraints. We explore two derived approaches, a proposal-based approach, and a heatmap-based approach, and we construct a dataset for evaluating the performance of the proposed approaches on image cropping under design constraints. In experiments, we demonstrate that the proposed approaches outperform a baseline, and we observe that the proposal-based approach is better than the heatmap-based approach under the same computation cost, but the heatmap-based approach leads to better scores by increasing computation cost. The experimental results indicate that balancing aesthetically plausible regions and satisfying design constraints is not a trivial problem and requires sensitive balance, and both proposed approaches are reasonable alternatives.

翻译：图像裁剪是图像编辑中获取构图增强图像的关键技术。在显示媒体领域，图像裁剪是自动生成媒体内容的前沿技术。然而，媒体内容的图像裁剪通常需要满足各种约束条件，例如宽高比以及为放置文字或对象预留空白区域。我们将此类问题称为设计约束下的图像裁剪。为实现在设计约束下的图像裁剪，我们提出了一种基于评分函数的方法，该方法能计算裁剪结果在美学合理性与设计约束满足度两方面的综合评分。我们探索了两种衍生方法：基于候选框的方法和基于热力图的方法，并构建了用于评估所提方法在设计约束下图像裁剪性能的数据集。实验表明，所提方法优于基准方法，且在同计算成本条件下，基于候选框的方法优于基于热力图的方法，但通过增加计算成本，基于热力图的方法可获得更优评分。实验结果揭示，平衡美学合理区域与设计约束满足度并非简单问题，需要精妙权衡，而两种方法均为合理选择。