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

arXiv: https://arxiv.org/abs/1707.09603 · HTML: https://mlsanity.com/paper/1707.09603/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jul 2017.

## Built on by (most cited first, 2 of 2)

- [The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions](https://mlsanity.com/paper/2304.09240/) (2023)
- [Full Body Video-Based Self-Avatars for Mixed Reality: from E2E System to User Study](https://mlsanity.com/paper/2208.12639/) (2022)

## Abstract (arXiv)

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 difficult 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 omni-directional mixed reality system using only the information from a monocular image sequence. We first present a semantic segmentation scheme for predicting the amount of visibility for different type of objects in the scene. We also simultaneously calculate a foreground probability map using depth estimation derived from optical flow. 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.