Reconstructing 3D Land Surface From a Sequence of Aerial Images

This paper proposes a method for reconstructing a 3D surface landscape from an aerial image sequence captured by a single noncalibrated camera. Reconstructing a 3D surface landscape is more difficult than constructing a landscape of buildings or objects in a room because of the lack of available information about camera parameters, the need for mosaicking of 3D surface elements, and the introduction of nonrigid objects. Therefore, conventional methods are not directly applicable. In order to solve these problems, we apply socalled 2-Dimensional Continuous Dynamic Programming (2DCDP) to obtain full pixel trajectories between successive image frames in a sequence of aerial images. Then we apply Tomasi–Kanade Factorization to the full pixel trajectories to reconstruct the 3D surface. We also develop a mosaicking technique for connecting all of the partially reconstructed surfaces. The experimental results show that our proposed method is very promising for reconstructing 3D surfaces, including a forest, a mountain, a lake and several houses. We conduct experiments to compare our method against a SIFT-based method using two sets of data, namely, artificial and real image sequence data.