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arXiv · 1608.04642

Temporally Consistent Motion Segmentation from RGB-D Video

Peter Bertholet·Alexandru-Eugen Ichim·Matthias Zwicker
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Abstract

We present a method for temporally consistent motion segmentation from RGB-D videos assuming a piecewise rigid motion model. We formulate global energies over entire RGB-D sequences in terms of the segmentation of each frame into a number of objects, and the rigid motion of each object through the sequence. We develop a novel initialization procedure that clusters feature tracks obtained from the RGB data by leveraging the depth information. We minimize the energy using a coordinate descent approach that includes novel techniques to assemble object motion hypotheses. A main benefit of our approach is that it enables us to fuse consistently labeled object segments from all RGB-D frames of an input sequence into individual 3D object reconstructions.

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Peter Bertholet, Alexandru-Eugen Ichim, Matthias Zwicker. 2016-08-16. Temporally Consistent Motion Segmentation from RGB-D Video. https://arxiv.org/abs/1608.04642

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