Accurate 3D model acquisition from imagery data

Acquisition of geometric 3D models from 2D imagery has been essential for various applications. In particular, this dissertation investigates two important application scenarios: city‐scale 3D reconstruction from aerial imagery and general 3D model acquisition with a commodity camera. ❧ The first part of this dissertation explores an online solution to the problem. We propose an approach to solve camera pose estimation and dense reconstruction from Wide Area Aerial Surveillance (WAAS) videos captured by an airborne platform. Our approach solves them in an online fashion: it incrementally updates a sparse 3D map and estimates the camera pose as each new frame arrives; depth maps of selected key frames are computed using a variational method and integrated to produce a full 3D model via volumetric reconstruction. In practice, aerial imagery is usually captured using a multi‐camera system. We propose an approach for camera pose estimation of multi‐camera aerial imagery which is parallelized on multiple GPUs for efficiency. The approach is also extended for progressive 3D model acquisition with a hand‐held camera. ❧ In many scenarios, online approach is not a necessity and accuracy has higher priority over efficiency. In the second part, we present MeshRecon, a mesh‐based offline system composed of three modules: a dense point cloud is generated using multi‐resolution plane sweep method; an initial mesh model is extracted from the point cloud via global optimization considering visibility information of all images; the mesh model is then iteratively refined to capture structural details by optimizing the photometric consistency and spatial regularization. The major processes are parallelized on GPU for efficiency. For the aerial imagery case, we evaluate our system on several real-world multi‐camera aerial imagery datasets, each covering an urban scenario of several square kilometers. Quantitative result shows that the reconstructed geometric 3D model is highly accurate with error smaller than 1 meter over the entire city. Besides aerial imagery, we also evaluate its performance on general geometric 3D model acquisition of real‐world objects. Result shows that the system is robust and flexible for various types of objects at different scales in both indoor and outdoor environments. Based on city 3D models reconstructed at different times, we present a system for city‐scale geometry change detection by performing comparisons at the 3D geometry level. Our system is able to detect geometry changes at different scales, ranging from a building cluster to small‐scale vegetation changes, with high accuracy. In the end, we conclude the dissertation with contributions and future work.