Revisiting Single-view Shape Tensors: Theory and Applications

Given the projection of a sufficient number of points it is possible to algebraically eliminate the camera parameters and obtain view-invariant functions of image coordinates and space coordinates. These single view invariants have been introduced in the past, however, they are not as well understood as their dual multi-view tensors. In this paper we revisit the dual tensors (bilinear, trilinear and quadlinear), both the general and the reference-plane reduced version,  and describe the complete set of synthetic constraints,
properties of the tensor slices, reprojection equations, non-linear constraints and reconstruction formulas.
We then apply some of the new results, such as the dual reprojection equations, for multi-view point tracking under occlusions with encouraging results.