Ensuring Safety in Augmented Reality from Trade-off Between Immersion and Situation Awareness
Ensuring Safety in Augmented Reality from Trade-off Between Immersion and Situation Awareness
复制标题
通过在沉浸感和态势感知之间进行权衡来确保增强现实的安全
DOI：
10.1109/ismar.2018.00032
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Wilko Heuten
中科院分区：
文献类型：
--
作者：
Jinki Jung;Hyeopwoo Lee;Jeehye Choi;Abhilasha Nanda;Uwe Gruenefeld;Tim Claudius Stratmann;Wilko Heuten
尽管增强现实(AR)的移动性和新兴技术在日常生活中带来了巨大的娱乐性和便利性，但由于沉浸在AR中导致的情况感知不足而导致的事故越来越多，AR的使用正在成为一个社会问题。在本文中，我们讨论了沉浸和情境感知之间的权衡，作为AR相关事故的根本因素。作为一种权衡的解决方案，我们提出了一种基于车辆位置估计(VPE)和车辆位置可视化(VPV)的第三方组件来预防交通环境中的人车事故。从RGB图像序列中，VPE使用生成的卷积神经网络(CNN)模型和基于感兴趣区域的方案有效地估计用户和汽车之间的相对3D位置。VPV使用视外对象可视化方法将估计的汽车位置显示为一个点，以警告用户可能发生的碰撞。16种参数组合的VPE实验表明，对激活图像进行微调的InceptionV3模型性能最好，在2.1ms内的均方根误差为0.34m。VPV的用户研究表明，AR游戏难度控制的沉浸感与情境感知的频率在数量和质量上都成反比关系。此外，评估两种视外物体可视化方法(EyeSee360和雷达)的VPV实验对参与者的活动没有显著影响，而EyeSee360产生了更快的反应，平均而言，雷达引起了参与者的偏好。我们的现场研究证明了VPE和VPV的集成，在日常使用中用于AR时，VPE和VPV具有安全保证浸泡的潜力。我们预计，当建议的组件开发到足以在现实世界中使用时，它将为确保安全的AR做出贡献，并为AR的人口做出贡献。
Although the mobility and emerging technology of augmented reality (AR) have brought significant entertainment and convenience in everyday life, the use of AR is becoming a social problem as the accidents caused by a shortage of situation awareness due to an immersion of AR are increasing. In this paper, we address the trade-off between immersion and situation awareness as the fundamental factor of the AR-related accidents. As a solution against the trade-off, we propose a third-party component that prevents pedestrian-vehicle accidents in a traffic environment based on vehicle position estimation (VPE) and vehicle position visualization (VPV). From a RGB image sequence, VPE efficiently estimates the relative 3D position between a user and a car using generated convolutional neural network (CNN) model with a region-of-interest based scheme. VPV shows the estimated car position as a dot using an out-of-view object visualization method to alert the user from possible collisions. The VPE experiment with 16 combinations of parameters showed that the InceptionV3 model, fine-tuned on activated images yields the best performance with a root mean squared error of 0.34 m in 2.1 ms. The user study of VPV showed the inversely proportional relationship between the immersion controlled by the difficulty of the AR game and the frequency of situation awareness in both quantitatively and qualitatively. Additional VPV experiment assessing two out-of-view object visualization methods (EyeSee360 and Radar) showed no significant effect on the participants' activity, while EyeSee360 yielded faster responses and Radar engendered participants' preference on average. Our field study demonstrated an integration of VPE and VPV which has potentials for safety-ensured immersion when the proposed component is used for AR in daily uses. We expect that when the proposed component is developed enough to be used in real world, it will contribute to the safety-ensured AR, as well as to the population of AR.
影响因子：
9.2
作者：
Geiger, A.;Lenz, P.;Urtasun, R.
通讯作者：
Urtasun, R.