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Simulation framework for improved UI/UX of AR-HUD display

Title
Simulation framework for improved UI/UX of AR-HUD display
Authors
Choi, Min-KookLee, Jin-HeeJung, HeechulTayibnapis, Iman RahmansyahKwon, Soon
DGIST Authors
Choi, Min-Kook; Kwon, Soon
Issue Date
2018-01-13
Citation
2018 IEEE International Conference on Consumer Electronics, ICCE 2018, 1-4
Type
Conference
ISBN
9781538630259
Abstract
The AR-HUD (Augmented Reality-Head Up Display) overlays the ADAS (Autonomous Driver Assistant System) information to real world objects on the windshield unlike the normal HUD. This projected ADAS information on the windshield usually occurs the irregularity between the objects and the ADAS information because of the difference between driver and AR-HUD's view plane. To overcome this problem, we present a simulation framework for the improved AR-HUD in ADAS by means of a homographie registration with inference outputs from a region based deep learning model. In order to build this simulation framework, we set up a simulation test bed to mimic on-road driving environment in a darkroom, and use the inference model based on region-based fully convolutional network to obtain on-road ADAS information. And then we apply the homographie registration method to minimize the irregularity between object and ADAS information in terms of driver's perception. We tested the proposed simulation framework with real world driving recordings, and it showed better display results for improved UI/UX with inference outputs from region-based deep learning model. © 2018 IEEE.
URI
http://hdl.handle.net/20.500.11750/8994
DOI
10.1109/ICCE.2018.8326307
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Kwon, Soon  
  • Research Interests computer vision; deep learning; autonomous driving; parallel processing; vision system on chip
Files:
There are no files associated with this item.
Collection:
Convergence Research Center for Future Automotive Technology2. Conference Papers


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