Bundle Adjustment — A Modern Synthesis

Authors

Bill Triggs, Philip F. McLauchlan, Richard I. Hartley, Andrew W. Fitzgibbon

Year

2000

Conference Paper

Algorithm

Bundle Adjustment

Source

Lecture Notes in Computer Science

Identifiers

DOI 10.1007/3-540-44480-7_21

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.

Summary¶

Synthesizes bundle adjustment for computer vision, covering robust cost functions, sparse Newton methods, gauge freedom, updating strategies, and quality control. The paper became a standard implementation-oriented reference for refining camera and structure estimates in photogrammetry and structure-from-motion pipelines.