Generation of virtual display surfaces for in-vehicle contextual augmented reality

In-vehicle contextual augmented reality (I-CAR) has the potential to provide novel visual feedback to drivers for an enhanced driving experience. To enable I-CAR, we present a parametrized road trench model (RTM) for dynamically extracting display surfaces from a driver´s point of view that is adaptable to constantly changing road curvature and intersections. We use computer vision algorithms to analyze and extract road features that are used to estimate the parameters of the RTM. GPS coordinates are used to quickly compute lighting parameters for shading and shadows. Novel driver-based applications that use the RTM are presented.