This paper proposes a method to recover the embedding
of the possible shapes assumed by a deforming nonrigid
object by comparing triplets of frames from an orthographic
video sequence. We assume that we are given features
tracked with no occlusions and no outliers but possible
noise, an orthographic camera and that any 3D shape of a
deforming object is a linear combination of several canonical
shapes. By exploiting any repetition in the object motion
and defining an ordering between triplets of frames in a
Generalized Non-Metric Multi-Dimensional Scaling framework,
our approach recovers the shape coefficients of the
linear combination, independently from other structure and
motion parameters. From this point, a good estimate of the
remaining unknowns is obtained for a final optimization to
perform full non-rigid structure from motion. Results are
presented on synthetic and real image sequences and our
method is found to perform better than current state of the
art.