Local bundle adjustment (LBA) has recently been introduced
to estimate the geometry of image sequences taken by
a calibrated camera. Its advantage over standard (global)
bundle adjustment is a great reduction of computational
complexity, which allows real-time performances with a
similar accuracy. However, no confidence measure on the
LBA result such as uncertainty or covariance has yet been
introduced. This paper introduces statistical models and estimation
methods for uncertainty with two desirable properties:
(1) uncertainty propagation along the sequence and
(2) real-time calculation. We also explain why this problem
is more complicated than it may appear at first glance, and
we provide results on video sequences.