论文标题
动态对象理解：评估人造视觉感知的框架
Dynamic Object Comprehension: A Framework For Evaluating Artificial Visual Perception
论文作者
论文摘要
增强现实和混合现实正在成为移动互联网的后继者。但是，仍然存在许多技术挑战。这些系统的关键要求之一是能够在物理和虚拟世界之间创建连续性，而用户的视觉感知是主要接口介质。建立这种连续性需要系统对物理世界的视觉理解。尽管在计算机视觉和AI技术（例如图像分类和对象检测）方面取得了重大进展，但这些领域的成功尚未导致这些关键的MR和AR应用所需的视觉感知。一个重要的问题是，当前的评估标准不足这些应用程序。为了激励和评估这个新兴领域的进步，需要新的指标。在本文中，我们概述了当前评估标准的局限性，并提出了新标准。
Augmented and Mixed Reality are emerging as likely successors to the mobile internet. However, many technical challenges remain. One of the key requirements of these systems is the ability to create a continuity between physical and virtual worlds, with the user's visual perception as the primary interface medium. Building this continuity requires the system to develop a visual understanding of the physical world. While there has been significant recent progress in computer vision and AI techniques such as image classification and object detection, success in these areas has not yet led to the visual perception required for these critical MR and AR applications. A significant issue is that current evaluation criteria are insufficient for these applications. To motivate and evaluate progress in this emerging area, there is a need for new metrics. In this paper we outline limitations of current evaluation criteria and propose new criteria.
