On-line Illumination Estimation of Outdoor Scenes Based on Area Selection for Augmented Reality

In augmented reality, consistent illumination plays an important role when integrating a virtual object into a video of real scene. In this paper, we propose a novel image based framework to estimate-on-line the dynamic ally changing illumination parameters of outdoor video sequences captured by a fixed camera. Unlike previous approaches which either request to know the scene geometry or involve huge storage to preserve time dependent basis images or statistic parameters, our approach requires very simple interaction at the initialization stage by a few brushes to select areas with specified surface normal, which are used to calculate the sunlight parameters. An optimization procedure is also applied, ensuring the robustness and precision of our estimation. Experimental results demonstrate the effectiveness and flexibility of the proposed approach.