National Natural Science Foundation of China (Grant Nos. 61305107, U1333109 and 61105096), the Fundamental Research Funds for the Central Universities (Grant No. ZXH2012N003), the Preresearch Major Project of Civil Aviation University of China (Grant No. 3122013P003), the Scientific Research Funds for Civil Aviation University of China (Grant No. 2012QD23X), and the Opening Project of State Key Laboratory of Robotics (Grant No. 2013-O02).
A novel error-aware visual localization method is proposed that utilizes vertical planes, such as vertical building facades in urban areas as landmarks. Vertical planes, reconstructed from coplanar vertical lines, are robust high-level features if compared with point features or line features. Firstly, the error models of vertical lines and vertical planes are built, where maximum likelihood estimation (MLE) is employed to estimate all vertical planes from coplanar vertical lines. Then, the closed-form representation of camera location error variance is derived. Finally, the minimum variance camera pose estimation is formulated into a convex optimization problem, and the weight for each vertical plane is obtained by solving this well-studied problem. Experiments are carried out and the results show that the proposed localization method has an accuracy of about 2 meters, at par with commercial GPS operating in open environments.