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.
