Surface Recovery Using Curvature and Motion Consistency

A key problem in the recovery of scene descriptions from multiple views is the fusion of information from di erent vantage points. The contribution of this paper is a set of algorithms for reconstructing surfaces obtained from overlapping range images in a common frame of reference. Surfaces are assumed to be piecewise-smooth but not necessarily rigid. Motion parameters, rotations and translations that describe correspondence between views, are recovered locally under the assumption that the curvature structure at a point on a surface varies slowly under transformation. The recovery problem can thus be posed as nding the set of motion parameters that preserves curvature across two views. We show that an appropriate similarity functional can be devised that is convex in the vicinity of the true motion parameters. This leads to an e cient local algorithm that recovers motion parameters in gradient descent fashion.