Issue No. 09 - September (2006 vol. 28)
R. Lerner , Dept. of Comput. Sci., Technion-Israel Inst. of Technol., Haifa
E. Rivlin , Dept. of Comput. Sci., Technion-Israel Inst. of Technol., Haifa
A novel algorithm for pose and motion estimation using corresponding features and a digital terrain map is proposed. Using a digital terrain (or digital elevation) map (DTM/DEM) as a global reference enables the elimination of the ambiguity present in vision-based algorithms for motion recovery. As a consequence, the absolute position and orientation of a camera can be recovered with respect to the external reference frame. In order to do this, the DTM is used to formulate a constraint between corresponding features in two consecutive frames. Explicit reconstruction of the 3D world is not required. When considering a number of feature points, the resulting constraints can be solved using nonlinear optimization in terms of position, orientation, and motion. Such a procedure requires an initial guess of these parameters, which can be obtained from dead-reckoning or any other source. The feasibility of the algorithm is established through extensive experimentation. Performance is compared with a state-of-the-art alternative algorithm, which intermediately reconstructs the 3D structure and then registers it to the DTM. A clear advantage for the novel algorithm is demonstrated in variety of scenarios
Motion estimation, Layout, Constraint optimization, Navigation, Digital cameras, Geometry, Stress, Image reconstruction, Image databases, Spatial databases
R. Lerner, E. Rivlin and H. Rotstein, "Pose and motion recovery from feature correspondences and a digital terrain map," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 28, no. 9, pp. 1404-1417, 2009.