Efficient annotation of image data sets for computer vision applications

Julia Möhrmann, G. Heidemann
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引用次数: 19

Abstract

High quality ground truth data sets are crucial for the development of image recognition systems. However, the task of annotating large image data sets manually takes a lot of time and effort. In order to lower the burden for the development of application-specific image recognition systems, we developed an advanced user interface. This interface is especially designed for non-expert users with little-to-no knowledge of computer vision techniques. The interface presents images clustered by similarity and allows for an efficient and simple annotation of large data sets. The integration of overview+detail concepts allows the precise navigation inside large data sets. The interface can be used without prior instructions on the underlying concepts, like self-organizing maps, image features or visualization techniques.
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计算机视觉应用中图像数据集的高效标注
高质量的地面真值数据集对于图像识别系统的发展至关重要。然而,手动注释大型图像数据集的任务需要花费大量的时间和精力。为了减轻特定应用图像识别系统的开发负担,我们开发了一个先进的用户界面。这个界面是特别为对计算机视觉技术知之甚少的非专业用户设计的。该界面根据相似性呈现图像,并允许对大型数据集进行有效而简单的注释。概览+细节概念的集成允许在大数据集中进行精确导航。无需事先说明基本概念,如自组织地图、图像特征或可视化技术,即可使用该界面。
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