Andreas Wedel, Annemarie Meißner, Clemens Rabe, Uwe Franke, Daniel CremersAbstractWe present an approach for identifying
and segmenting independently moving objects from dense scene flow
information, using a moving stereo camera system. The detection and
segmentation is challenging due to camera movement and non-rigid object
motion. The disparity, change in disparity, and the optical flow are
estimated in the image domain and the three-dimensional motion is
inferred from the binocular triangulation of the translation vector.
Using error propagation and scene flow reliability measures, we assign
dense motion likelihoods to every pixel of a reference frame. These
likelihoods are then used for the segmentation of independently moving
objects in the reference image. In our results we systematically
demonstrate the improvement using reliability measures for the scene
flow variables. Furthermore, we compare the binocular segmentation of
independently moving objects with a monocular version, using solely the
optical flow component of the scene flow. [Download] [View] [BibTeX] |
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