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Bundle Ajustment -- A Modern Synthesis

Bill Triggs 1 Philip Mclauchlan 2 Richard Hartley 3 Andrew Fitzgibbon 4 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : This paper is a survey of the theory and methods of photogrammetric bundle adjustment, aimed at potential implementors in the computer vision community. Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal structure and viewing parameter estimates. Topics covered include: the choice of cost function and robustness; numerical optimization including sparse Newton methods, linearly convergent approximations, updating and recursive methods; gauge (datum) invariance; and quality control. The theory is developed for general robust cost functions rather than restricting attention to traditional nonlinear least squares.
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Submitted on : Tuesday, May 3, 2011 - 9:24:38 AM
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Bill Triggs, Philip Mclauchlan, Richard Hartley, Andrew Fitzgibbon. Bundle Ajustment -- A Modern Synthesis. Bill Triggs and Andrew Zisserman and Richard Szeliski. Vision Algorithms: Theory and Practice, 1883, Springer-Verlag, pp.298--372, 2000, Lecture Notes in Computer Science (LNCS), ⟨10.1007/3-540-44480-7_21⟩. ⟨inria-00590128⟩



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