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Abstract(s)
In this paper we propose a novel fully probabilistic
solution to the stereo egomotion estimation problem. We extend
the notion of probabilistic correspondence to the stereo case
which allow us to compute the whole 6D motion information in
a probabilistic way. We compare the developed approach against
other known state-of-the-art methods for stereo egomotion estimation,
and the obtained results compare favorably both for the
linear and angular velocities estimation.
Description
Keywords
Angular velocity Cameras Estimation Probabilistic logic Robot sensing systems Visualization