A factorization approach to structure from motion with shape priors

This paper presents an approach for including 3D prior models into a factorization framework for structure from motion. The proposed method computes a closed-form affine fit which mixes the information from the data and the 3D prior on the shape structure. Moreover, it is general in regards to different classes of objects treated: rigid, articulated and deformable. The inclusion of the shape prior may aid the inference of camera motion and 3D structure components whenever the data is degenerate (i.e. nearly planar motion of the projected shape). A final non-linear optimization stage, which includes the shape priors as a quadratic cost, upgrades the affine fit to metric. Results on real and synthetic image sequences, which present predominant degenerate motion, make clear the improvements over the 3D reconstruction.