Efficient and robust radiance transfer for probeless photorealistic augmented reality

Photorealistic Augmented Reality (AR) requires knowledge of the scene geometry and environment lighting to compute photometric registration. Recent work has introduced probeless photometric registration, where environment lighting is estimated directly from observations of reflections in the scene rather than through an invasive probe such as a reflective ball. However, computing the dense radiance transfer of a dynamically changing scene is computationally challenging. In this work, we present an improved radiance transfer sampling approach, which combines adaptive sampling in image and visibility space with robust caching of radiance transfer to yield real time framerates for photorealistic AR scenes with dynamically changing scene geometry and environment lighting.