Towards Universal Evaluation of Image Annotation Interfaces

Andrew M. Vernier, Jean Y. Song, Edward Sun, A. Kench, Walter S. Lasecki
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引用次数: 1

Abstract

To guide the design of interactive image annotation systems that generalize to new domains and applications, we need ways to evaluate the capabilities of new annotation tools across a range of different types of image, content, and task domains. In this work, we introduce Corsica, a test harness for image an- notation tools that uses calibration images to evaluate a tool's capabilities on general image properties and task requirements. Corsica is comprised of sets of three key components: 1) synthesized images with visual elements that are not domain- specific, 2) target microtasks that connects the visual elements and tools for evaluation, and 3) ground truth data for each mi- crotask and visual element pair. By introducing a specification for calibration images and microtasks, we aim to create an evolving repository that allows the community to propose new evaluation challenges. Our work aims to help facilitate the robust verification of image annotation tools and techniques.
图像标注接口的通用评价
为了指导可推广到新领域和应用程序的交互式图像注释系统的设计,我们需要评估跨一系列不同类型的图像、内容和任务领域的新注释工具的能力的方法。在这项工作中,我们介绍了Corsica,这是一个用于图像标记工具的测试工具,它使用校准图像来评估工具在一般图像属性和任务要求上的能力。Corsica由三个关键组件组成:1)非特定领域的视觉元素合成图像,2)连接视觉元素和评估工具的目标微任务,以及3)每个mi- crotask和视觉元素对的真实数据。通过引入校准图像和微任务的规范,我们的目标是创建一个不断发展的存储库,允许社区提出新的评估挑战。我们的工作旨在帮助促进图像标注工具和技术的鲁棒性验证。
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