Hierarchical depth estimation for image synthesis in mixed reality

Mixed reality is different from the virtual reality in that users can feel immersed in a space which is composed of not only virtual but also real objects. Thus, it is essential to realize seamless integration and mutual occlusion of the virtual and real worlds. Therefore, we need depth information of the real scene to perform the synthesis. We propose the depth estimation algorithm with sharp object boundaries for mixed reality system based on hierarchical disparity estimation. Initial disparity vectors are obtained from downsampled stereo images using region-dividing disparity estimation technique. Then, background region is detected and flattened. With these initial vectors, dense disparities are estimated and regularized with shape-adaptive window in full resolution images. Finally, depth values are calculated by stereo geometry and camera parameters. As a result, virtual objects can be mixed into the image of real world by comparing the calculated depth values with the depth information of generated virtual objects. Experimental results show that occlusion between the virtual and real objects are correctly established with sharp boundaries in the synthesized images, so that user can observe the mixed scene with considerably natural sensation.