Instant Panoramic Texture Mapping with Semantic Object Matching for Large-Scale Urban Scene Reproduction.

This paper proposes a novel panoramic texture mapping-based rendering system for real-time, photorealistic reproduction of large-scale urban scenes at a street level. Various image-based rendering (IBR) methods have recently been employed to synthesize high-quality novel views, although they require an excessive number of adjacent input images or detailed geometry just to render local views. While the development of global data, such as Google Street View, has accelerated interactive IBR techniques for urban scenes, such methods have hardly been aimed at high-quality street-level rendering.