Automotive augmented reality 3D head-up display based on light-field rendering with eye-tracking
Jinho Lee, Igor Yanusik, Yoonsun Choi, Byongmin Kang, Chansol Hwang, Juyong Park, Dongkyung Nam, Sung‐Hoon Hong
Abstract
We explore the feasibility of implementing stereoscopy-based 3D images with an eye-tracking-based light-field display and actual head-up display optics for automotive applications. We translate the driver's eye position into the virtual eyebox plane via a "light-weight" equation to replace the actual optics with an effective lens model, and we implement a light-field rendering algorithm using the model-processed eye-tracking data. Furthermore, our experimental results with a prototype closely match our ray-tracing simulations in terms of designed viewing conditions and low-crosstalk margin width. The prototype successfully delivers virtual images with a field of view of 10° × 5° and static crosstalk of <1.5%.