In this paper, we propose a robust algorithm that estimates
3-D motion parameters and scene depth with calibrated
stereo image sequences. Compared with the previous linear
or least squares methods using the direct method, the proposed
method is robust to the structured noises, which are
dependent on the contents of image such as intensity edges,
depth discontinuities and occluded areas. With respect to
the hierarchical motion estimation framework, an effective
method for determining the number of iterative refinements
is also suggested by using the robust estimation framework.
Computer simulation with a synthetic image sequence and
experiments with real image sequences show that the proposed
algorithm has performed better, compared with the
existing methods.
3-D motion parameters and scene depth with calibrated
stereo image sequences. Compared with the previous linear
or least squares methods using the direct method, the proposed
method is robust to the structured noises, which are
dependent on the contents of image such as intensity edges,
depth discontinuities and occluded areas. With respect to
the hierarchical motion estimation framework, an effective
method for determining the number of iterative refinements
is also suggested by using the robust estimation framework.
Computer simulation with a synthetic image sequence and
experiments with real image sequences show that the proposed
algorithm has performed better, compared with the
existing methods.