Least-Squares Minimization Under Constraints
نویسندگان
چکیده
These algorithms are, however, not designed to perform least-squares minimization under hard constraints. This short report outlines two very simple approaches to doing this to solve problems such as the one depicted by Fig. 1. The first relies on standard Lagrange multipliers [Boyd and Vandenberghe, 2004]. The second is inspired by inverse kinematics techniques [Baerlocher and Boulic, 2004] and has been demonstrated for the purpose of monocular 3D surface modeling in [Salzmann and Fua, 2010]. In both cases, we outline matlab implementations.
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