ActiveAR: Augmented Reality Task Support System with Proactive Context and Virtual Content Management.

Renjie Zhang, Jia Liu, Taishi Sawabe, Yuichiro Fujimoto, Masayuki Kanbara, Hirokazu Kato
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Abstract

Augmented Reality (AR) has long been expected to help users improve their working efficiency. However, due to the absence of intelligent systems, existing AR applications are greatly affected by the virtual content interference with real-world activities. Unlike existing work, which focuses more on hiding virtual content to reduce interference, in this work, we propose an innovative AR Task Support System where virtual contents actively guide users with task completion. During task execution, our system proactively searches for and tracks key objects in the scene, and uses this context information to automatically select appropriate virtual content and display positions. Through introducing open-world prompt-based visual models, our system can effectively retrieve few-shot or even zero-shot objects that are uncommon in the dataset. This approach extends the use of AR Task Support System beyond controlled industrial settings to more uncontrolled daily scenarios, overcoming the limitations of existing systems. It also significantly reduces development costs for developers. We demonstrate the advantages of our system over traditional virtual content management systems through a series of experiments that are closer to users' real usage situations.

ActiveAR:具有主动上下文和虚拟内容管理的增强现实任务支持系统。
人们一直期望增强现实(AR)能够帮助用户提高工作效率。然而,由于缺乏智能系统,现有的AR应用受到虚拟内容与现实世界活动干扰的极大影响。与现有工作更多地侧重于隐藏虚拟内容以减少干扰不同,在这项工作中,我们提出了一种创新的AR任务支持系统,虚拟内容主动引导用户完成任务。在任务执行过程中,我们的系统会主动搜索和跟踪场景中的关键对象,并使用这些上下文信息自动选择合适的虚拟内容和显示位置。通过引入基于开放世界提示的视觉模型,我们的系统可以有效地检索到数据集中不常见的少拍甚至零拍对象。这种方法将AR任务支持系统的使用范围从受控的工业环境扩展到更不受控制的日常场景,克服了现有系统的局限性。它还大大降低了开发人员的开发成本。我们通过一系列更接近用户实际使用情况的实验,展示了我们的系统相对于传统虚拟内容管理系统的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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