Implicit, view invariant, linear flexible shape modelling

Flexible shape modelling in which the image of an object is represented by a finite set of landmark points is briefly reviewed. It is argued that variation in the apparent size and shape of the image of an object with change of viewpoint are extrinsic variations and that, under weak or para-perspective imaging, such changes should be taken into account by using the affine trifocal tensor to provide a mapping between image triplets. It is shown how the Procrustes error may be extended to accommodate such mappings, how the remaining intrinsic variations may be extracted, a pair of virtual basis views derived, and a statistical model constructed. An Integrated Shape and Pose Model (ISPM) that integrates a hierarchical principal components analysis model with a multi-view geometry model, was constructed and shown, on data from a small database of face images, to outperform previous models.