TEXTURING LONG PLANAR SURFACES WITH IMPRECISE CAMERA POSES FOR INDOOR 3D MODELING

摘要: Automated 3D modeling of building interiors is useful in applications such as virtual reality and environment mapping. Texture mapping walls is an important step in visualizing the results of an indoor 3D modeling system. Methods to localize the camera in the 3D scene often are not pixel accurate, meaning that when multiple images are used for texture mapping there are seams and discontinuities between these images. Several approaches to this problem have been proposed but each suffer from a distinct problem of error accumulation for long chains of images, such as those from a long corridor. We propose a new approach to texture mapping planar surfaces that eliminates discontinuities between images but does not suffer from error accumulation for long chains. We validate this approach using images from several long hallways with data generated by a human operated backpack 3D indoor modeling system.