Optimal algorithms in multiview geometry

Authors:
Richard Hartley;Fredrik Kahl
Affiliations:
Research School of Information Sciences and Engineering, The Australian National University, National ICT Australia;Centre for Mathematical Sciences, Lund University, Sweden
Venue:
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Year:
2007

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Abstract

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 L2 (least-squares) or L∞ (smallest maximum error) norm. The main methods involve Second Order Cone Programming, or quasi-convex optimization, and Branch-andbound. 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.