@unpublished{Jin2018,Author = {Jinki Jung, Hyeopwoo Lee, Jeehye Choi, Abhilasha Nanda, Uwe Gruenefeld, Tim Claudius Stratmann, Wilko Heuten},Title = {Ensuring Safety in Augmented Reality from Trade-off Between Immersion and Situation Awareness},Year = {2018},Month = {10},type = {unpublished},Abstract = {Although the mobility and emerging technology of augmented reality (AR) have brought significant entertainment and convenience in everyday life,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.}}@COMMENT{Bibtex file generated on }