The authors describe an algorithm based on hierarchical model-based estimation and refinement that aims to make best use of the information in stereo and motion data sets to estimate scene structure. Information from both data sets is used to compute simultaneously stereo and motion correspondences that are consistent with a single scene structure. One result is that local ambiguities in information provided by one data set are resolved by information provided by the other data set. The algorithm uses an infinitesimal rigid-body motion model to estimate relative camera orientation and local ranges for both the stereo and motion components of the data. If the relative orientation of the cameras in the stereo data set is known, the solution proposed can be re-derived using fixed rather than variable camera parameters for the stereo data set.
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