Model-guided 3D stitching for augmented virtual environment

Image and video stitching have made tremendous progress in the construction of wide field-of-view (FOV). However, some long-term challenges still exist, including wide baselines between cameras, large parallaxes, and low texture in overlapping areas. The augmented virtual environment (AVE) captures videos as live textures of 3D models in a virtual environment, and provides another 3D solution to overcome the aforementioned challenges. Existing AVE methods primarily follow from video projection, and cannot produce satisfactory stitching results compared with image stitching. In this paper, we propose a novel model-guided 3D stitching algorithm for AVE. The algorithm recovers an approximate 3D model for each video streaming and optimizes the warping of the models to meet the requirements of feature point matching of the 3D models from adjacent videos. Compared with previous state-of-the-art methods, experiment results illustrate that our method significantly improves the stitching quality.