3-D SCENE RECONSTRUCTION FROM MONOCULAR IMAGE SEQUENCES
Milan Hanajík - Paul P. J. van den Bosch
In this paper we deal with the problem of 3-D scene description
reconstruction from monocular image sequences.
The reconstruction is based on the processing of linear features
extracted from the acquired images.
Two reconstruction algorithms are introduced. The first one
formulates the problem as the stochastic filtering problem and the
algorithm computes the scene description incrementally using the
Extended Kalman Filter (EKF).
Issues of the computational complexity of the algorithm are
addressed and an algorithm with computation time in each iteration
step linearly proportional to the number of processed line
segments is proposed.
The second algorithm formulates the problem as the global
optimization problem, and the maximum likelihood estimate
(MLE) of the scene is numerically computed from all images
in one batch.
Results achieved with a sample image sequence are given
and conclusions are derived.
Keywords: 3-D structure from motion, Extended Kalman Filter, computational complexity