Saliency Based Image Cropping

Image cropping is a technique that is used to select the most relevant areas of an image and discarding the useless parts. Handmade selection, especially in case of large photo collections, is a time consuming task. Automatic image cropping techniques may help users, suggesting to them which part of the image is the most relevant, according to specific criteria. In this paper we suppose that the most visually salient areas of a photo are also the most relevant ones to the users. We compare three different saliency detection methods within an automatic image cropping system, to study the effectiveness of the related saliency maps for this task. We furthermore extended one of the three methods (our previous work), which is based on the extraction of keypoints from the image. Tests have been conducted onto an online available dataset, made of 5000 images which have been manually labeled by 9 users

Image Cropping under Design Constraints

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.Comment: ACMMM Asia accepte