Geometry and Texture from Thousands of Images

摘要

This paper presents a novel method for automatically recovering dense surface patches using large sets (1000's) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Some of the most important characteristics of our approach are that it: (1) uses and refines noisy calibration estimates; (2) compensates for large variations in illumination; (3) tolerates significant soft occlusion (e.g. tree branches); and (4) associates, at a fundamental level, an estimated normal (eliminating the frontal-planar assumption) and texture with each surface patch.