Optimization on shape curves with application to specular stereo

We state that a one-dimensional manifold of shapes in 3-space can be modeled by a level set function. Finding a minimizer of an independent functional among all points on such a shape curve has interesting applications in computer vision. It is shown how to replace the commonly encountered practice of gradient projection by a projection onto the curve itself. The outcome is an algorithm for constrained optimization, which, as we demonstrate theoretically and numerically, provides some important benefits in stereo reconstruction of specular surfaces.