Computer Vision for International Border Legibility
Computer Vision for International Border Legibility
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DOI：
10.1109/wacv56688.2023.00383
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发表时间：
2023-01
期刊：
影响因子：
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通讯作者：
Trevor Ortega;Thomas Nelson;Skyler Crane;Josh Myers-Dean;Scott Wehrwein
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文献类型：
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作者：
Trevor Ortega;Thomas Nelson;Skyler Crane;Josh Myers-Dean;Scott Wehrwein
国际政策的关键方面，如与移徙和贸易有关的方面，表现在国际政治边界的实际世界中；因此，研究这些政策的影响和影响的政治科学对边界很感兴趣。虽然之前的一些努力已经使用训练有素的人类编码员和众包来描述边界的特征，但由于需要手动注释，这些努力在规模上受到限制。在本文中，我们提出了一种新的任务、数据集和基线方法，用于在全球范围内自动估计国际政治边界的可读性。我们的贡献是(1)定义边界清晰度估计任务；(2)收集整个世界国际边界的空中(航空)图像的数据集；(3)提出几种经典的基于深度学习的方法来建立任务的基线；(4)针对众包清晰度比较的验证数据集来评估我们的算法。我们在这项具有挑战性的任务上的结果证实，虽然低级特征通常可以解释边界的易读性，但中级和高级特征也很重要。最后，我们展示了全球可读性分析的初步结果，证实了可读性的一些政治和地理影响。
Key aspects of international policy, such as those pertaining to migration and trade, manifest in the physical world at international political borders; for this reason, borders are of interest to political science studying the impacts and implications of these policies. While some prior efforts have worked to characterize features of borders using trained human coders and crowdsourcing, these are limited in scale by the need for manual annotations. In this paper, we present a new task, dataset, and baseline approaches for estimating the legibility of international political borders automatically and on a global scale. Our contributions are to (1) define the border legibility estimation task; (2) collect a dataset of overhead (aerial) imagery for the entire world’s international borders, (3) propose several classical and deep-learning-based approaches to establish a baseline for the task, and (4) evaluate our algorithms against a validation dataset of crowdsourced legibility comparisons. Our results on this challenging task confirm that while low-level features can often explain border legibility, mid- and high-level features are also important. Finally, we show preliminary results of a global analysis of legibility, confirming some of the political and geographic influences of legibility.