Pose and motion recovery from feature correspondences and a digital terrain map.
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.
Lerner
Ronen
R
Department of Computer Science, Technion-Israel Institute of Technology, Haifa 32000, Israel. ronenl@cs.technion.ac.il
Rivlin
Ehud
E
Rotstein
Héctor P
HP
D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D010780:Photogrammetry / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted