MATCHING TERRESTRIAL IMAGES CAPTURED BY A NOMAD SYSTEM TO IMAGES OF A REFERENCE DATABASE FOR POSE ESTIMATION PURPOSE

Mobile mapping systems have been developed to achieve a fast automated acquisition of huge quantity of georeferenced terrestrial images in urban cities. Stereopolis is such a system making it possible to capture panoramic groups of images. These georeferenced photos are then stored in urban images street scale reference databases. The issue investigated in this paper is the problem of tie points extraction between new images captured with an approximate georeferencement by a ”nomad system” and images from the reference database in order to estimate a precise pose for these new images. Because of several difficulties (diachronism, viewpoint change, scale variation, repetitive patterns) extracting enough correct well distributed tie points is difficult and directly extracted and matched SIFT keypoints from original images are most of the time not sufficient. Nevertheless, results can be improved using ortho-rectified images on the facade plane instead of original images. Rectification parameters (3D rotation) are obtained from the coordinates of vanishing points corresponding to the two main directions of the facade. These points can indeed be extracted from linear features of the facade on the images. However, many point matches remain false and difficult to detect using only their image coordinates. The use of both image coordinates and scale and orientation associated to the matched SIFT keypoints makes it possible to detect outliers and to obtain an approximate similitude model between the two ortho-images. A more accurate model can then be computed from correct tie points.