Uwe Franke, Clemens RabeAbstractThe extraction of depth is a
prerequisite for many applications in robotics and driver assistance.
Examples are obstacle detection, collision avoidance, and parking. This
paper presents a new Kalman filter based depth from motion approach.
Thanks to multiple filters running in parallel the rate of convergence
is significantly higher than in direct methods, especially if the
vehicle drives slowly. A goodness-of-fit test fuses the states of the
different filters in an optimum manner. In addition, this test allows to
distinguish between static and moving obstacles.
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