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Recursive 3-D Visual Motion Estimation Using Subspace Constraints
Authors:Soatto  Stefano  Perona  Pietro
Affiliation:(1) Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK
Abstract:A structure from motion algorithm is described which recovers structure and camera position, modulo a projective ambiguity. Camera calibration is not required, and camera parameters such as focal length can be altered freely during motion. The structure is updated sequentially over an image sequence, in contrast to schemes which employ a batch process. A specialisation of the algorithm to recover structure and camera position modulo an affine transformation is described, together with a method to periodically update the affine coordinate frame to prevent drift over time. We describe the constraint used to obtain this specialisation.Structure is recovered from image corners detected and matched automatically and reliably in real image sequences. Results are shown for reference objects and indoor environments, and accuracy of recovered structure is fully evaluated and compared for a number of reconstruction schemes. A specific application of the work is demonstrated—affine structure is used to compute free space maps enabling navigation through unstructured environments and avoidance of obstacles. The path planning involves only affine constructions.
Keywords:dynamic vision  recursive rigid motion estimation  nonlinear identification  implicit Extended Kalman Filter
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