Vol. 34/9, pp1713-1728
In this paper, we propose a robust algorithm that estimates 3-D motion parameters and scene depth with calibrated
stereo image sequences. In the direct method based on the brightness change constraint equation, we show that the
previous linear or least-squares methods are prone to error about the structured noises which are dependent on the
contents of image such as intensity edges, depth discontinuities and occluded areas. We also show that the proposed
algorithm is robust to those error distributions. With respect to the hierarchical motion estimation framework, an
e!ective method for determining the number of iterative re"nements, which a!ects the accuracy of 3-D motion
estimation, is also suggested by using the proposed robust estimation framework. Computer simulation with a synthetic
image sequence and experiments with various real-image sequences show that the proposed algorithm has improved the
estimation accuracy, compared with existing least-squares methods.
In this paper, we propose a robust algorithm that estimates 3-D motion parameters and scene depth with calibrated
stereo image sequences. In the direct method based on the brightness change constraint equation, we show that the
previous linear or least-squares methods are prone to error about the structured noises which are dependent on the
contents of image such as intensity edges, depth discontinuities and occluded areas. We also show that the proposed
algorithm is robust to those error distributions. With respect to the hierarchical motion estimation framework, an
e!ective method for determining the number of iterative re"nements, which a!ects the accuracy of 3-D motion
estimation, is also suggested by using the proposed robust estimation framework. Computer simulation with a synthetic
image sequence and experiments with various real-image sequences show that the proposed algorithm has improved the
estimation accuracy, compared with existing least-squares methods.