@inproceedings{PB-VRVis-2017-041,
author = {Mohr, Peter and Tatzgern, Markus and Grubert, Jens and Schmalstieg, Dieter and Kalkofen, Denis},
title = {Adaptive user perspective rendering for Handheld Augmented Reality},
year = {2017},
booktitle = {2017 IEEE Symposium on 3D User Interfaces (3DUI)},
editor = {Marchal, Maud and Teather, Robert J. and Bruce, Thomas},
doi = {10.1109/3DUI.2017.7893336},
url = {https://www.vrvis.at/publications/PB-VRVis-2017-041},
publisher = {IEEE},
isbn = {978-1-5090-6716-9},
pages = {176--181},
abstract = {Handheld Augmented Reality commonly implements some variant of  magic lens rendering, which turns only a fraction of the users  real environment into AR while the rest of the environment  remains unaffected. Since handheld AR devices are commonly  equipped with video see-through capabilities, AR magic lens  applications often suffer from spatial distortions, because the  AR environment is presented from the perspective of the camera  of the mobile device. Recent approaches counteract this  distortion based on estimations of the users head position,  rendering the scene from the user's perspective. To this end,  approaches usually apply face-tracking algorithms on the front  camera of the mobile device. However, this demands high  computational resources and therefore commonly affects the  performance of the application beyond the already high  computational load of AR applications. In this paper, we present  a method to reduce the computational demands for user  perspective rendering by applying lightweight optical flow  tracking and an estimation of the users motion before head  tracking is started. We demonstrate the suitability of our  approach for computationally limited mobile devices and we  compare it to device perspective rendering, to head tracked user  perspective rendering, as well as to fixed point of view user  perspective rendering.},
}