Shape and Motion of 3-D Curves from Multi–View Image Sequences

We introduce a framework for recovering the 3D motion and shape of unknown, moving curves from two or more image sequences acquired simultaneously from distinct points in space. We use this framework to (1) identify ambiguities in the multiview recovery of 3D motion for arbitrary curves, and (2) identify a novel spatio-temporal constraint that couples the problems of 3D shape and 3D motion recovery in the multi-view case. We show that this constraint leads to a simple algorithm for estimating 3D curve motion and 3D shape simultaneously. Experiments performed with synthetic data suggest that the algorithm allows accurate recovery of 3D curve motion, and yields shape estimates of higher accuracy than those obtained when stereo analysis alone is applied to simultaneous snapshots of a multi-view sequence.