TY - GEN
T1 - First attempt to build realistic driving scenes using video-to-video synthesis in OpenDS framework
AU - Song, Zili
AU - Wang, Shuolei
AU - Peng, Xiangjun
AU - Kong, Weikai
AU - Sun, Xu
N1 - Publisher Copyright:
© 2019 Copyright is held by the owner/author(s).
PY - 2019/9/21
Y1 - 2019/9/21
N2 - Existing programmable simulators enable researchers to customize different driving scenarios to conduct in-lab automotive driver simulations. However, software-based simulators for cognitive research generate and maintain their scenes with the support of 3D engines, which may affect users’ experiences to a certain degree since they are not sufficiently realistic. Now, a critical issue is the question of how to build scenes into real-world ones. In this paper, we introduce the first step in utilizing video-to-video synthesis, which is a deep learning approach, in OpenDS framework, which is an open-source driving simulator software, to present simulated scenes as realistically as possible. Off-line evaluations demonstrated promising results from our study, and our future work will focus on how to merge them appropriately to build a close-to-reality, real-time driving simulator.
AB - Existing programmable simulators enable researchers to customize different driving scenarios to conduct in-lab automotive driver simulations. However, software-based simulators for cognitive research generate and maintain their scenes with the support of 3D engines, which may affect users’ experiences to a certain degree since they are not sufficiently realistic. Now, a critical issue is the question of how to build scenes into real-world ones. In this paper, we introduce the first step in utilizing video-to-video synthesis, which is a deep learning approach, in OpenDS framework, which is an open-source driving simulator software, to present simulated scenes as realistically as possible. Off-line evaluations demonstrated promising results from our study, and our future work will focus on how to merge them appropriately to build a close-to-reality, real-time driving simulator.
KW - Driving simulator
KW - Machine learning
KW - Video synthesis
UR - http://www.scopus.com/inward/record.url?scp=85073631555&partnerID=8YFLogxK
U2 - 10.1145/3349263.3351497
DO - 10.1145/3349263.3351497
M3 - Conference contribution
AN - SCOPUS:85073631555
T3 - Adjunct Proceedings - 11th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019
SP - 387
EP - 391
BT - Adjunct Proceedings - 11th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019
PB - Association for Computing Machinery, Inc
T2 - 11th ACM International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2019
Y2 - 21 September 2019 through 25 September 2019
ER -