基于形状感知切片与优化的任意形状图像拼贴
Image Collage on Arbitrary Shape via Shape-Aware Slicing and Optimization
AI总结：
本文提出一种基于中轴和二叉切片树的 Shape-Aware Slicing 算法与优化方案，通过最大化图像显著区域，实现任意形状上的高效图像拼贴，视觉效果优于现有方法。
摘要：
图像拼贴是可视化图像集合的非常有用的工具。大多数现有的生成图像拼贴的方法和商业应用都设计于简单形状，例如矩形和圆形布局。这极大地限制了图像拼贴在一些艺术和创意场景中的使用。尽管有一些方法可以生成不规则形状的图像拼贴，但它们通常存在严重的图像重叠和过多的空白空间。这阻碍了此类方法成为有效的信息交流工具。在本文中，我们提出了一种形状切片算法和一种优化方案，该方案能够在给定输入形状和图像集合的情况下，以信息丰富且视觉愉悦的方式创建任意形状的图像拼贴。为了克服不规则形状的挑战，我们提出了一种名为 Shape-Aware Slicing 的新算法，该算法基于中轴和二叉切片树将输入形状划分为单元格。Shape-Aware Slicing 专门针对不规则形状设计，考虑了人类感知和形状结构，以生成视觉愉悦的划分。然后，通过分析输入图像来优化布局，目标是最大化图像的总显著区域。为了评估我们的方法，我们进行了大量实验，并将我们的结果与先前的工作进行了比较。评估表明，我们提出的算法能够高效地在不规则形状上排列图像集合，并创造出比先前工作和现有商业工具更具视觉优越性的结果。
英文摘要：
Image collage is a very useful tool for visualizing an image collection. Most of the existing methods and commercial applications for generating image collages are designed on simple shapes, such as rectangular and circular layouts. This greatly limits the use of image collages in some artistic and creative settings. Although there are some methods that can generate irregularly-shaped image collages, they often suffer from severe image overlapping and excessive blank space. This prevents such methods from being effective information communication tools. In this paper, we present a shape slicing algorithm and an optimization scheme that can create image collages of arbitrary shapes in an informative and visually pleasing manner given an input shape and an image collection. To overcome the challenge of irregular shapes, we propose a novel algorithm, called Shape-Aware Slicing, which partitions the input shape into cells based on medial axis and binary slicing tree. Shape-Aware Slicing, which is designed specifically for irregular shapes, takes human perception and shape structure into account to generate visually pleasing partitions. Then, the layout is optimized by analyzing input images with the goal of maximizing the total salient regions of the images. To evaluate our method, we conduct extensive experiments and compare our results against previous work. The evaluations show that our proposed algorithm can efficiently arrange image collections on irregular shapes and create visually superior results than prior work and existing commercial tools.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
