Occlusion Handling using Semantic Segmentation and Visibility-Based Rendering for Mixed Reality

Real-time occlusion handling is a major problem in outdoor mixed reality system because it requires great computational cost mainly due to the complexity of the scene. Using only segmentation, it is dicult to accurately render a virtual object occluded by complex objects such as trees, bushes etc. In this paper, we propose a novel occlusion handling method for real-time, outdoor, and omnidirectional mixed reality system using only the information from a monocular image sequence. We €rst present a semantic segmentation scheme for predicting the amount of visibility for di‚erent type of objects in the scene. We also simultaneously calculate a foreground probability map using depth estimation derived from optical ƒow. Finally, we combine the segmentation result and the probability map to render the computer generated object and the real scene using a visibility-based rendering method. Our results show great improvement in handling occlusions compared to existing blending based methods.