Abstract
An edge-based trinocular stereovision algorithm is presented. The
primitives it works on are cubic B-spline approximations of the 2-D
edges. This allows one to deal conveniently with curvature and to extend
to some nonpolyhedral scenes to previous stereo algorithms. To build a
matching primitive, the principle of the algorithm is, first, to find a
triplet of corresponding points on three splines. This is provided by
the bootstrapping part. Second, the algorithm propagates along the three
supporting splines to find other matching points. This provides a set of
ordered point triplets along these three splines, for which all the
matching constraints are verified. This primitive constitutes a
trinocular hypothesis. The set of all hypotheses is obtained by
propagating from all the point triplets provided by the bootstrapping
process. A criterion based on the size of the hypotheses is then used to
choose among them a compatible set with respect to the uniqueness
constraint. Results of several 3-D reconstructed scenes are shown
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