Optimal algorithms in multiview geometry

This is a survey paper summarizing recent research aimed at finding guaranteed optimal algorithms for solving problems in Multiview Geometry. Many of the traditional problems in Multiview Geometry now have optimal solutions in terms of minimizing residual imageplane error. Success has been achieved in minimizing L-2 (least-squares) or L-infinity (smallest maximum error) norm. The main methods involve Second Order Cone Programming, or quasi-convex optimization, and Branch-and-bound. The paper gives an overview of the subject while avoiding as far as possible the mathematical details, which can be found in the original papers.