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Segmentation is an important preprocessing step in many applications.
Compared to colour segmentation, fusion of colour and depth
greatly improves the segmentation result. Such a fusion is easy to do by
stacking measurements in di erent value dimensions, but there are better
ways. In this paper we perform fusion using the channel representation,
and demonstrate how a state-of-the-art segmentation algorithm can be
modi ed to use channel values as inputs. We evaluate segmentation results
on data collected using the Microsoft Kinect peripheral for Xbox
360, using the superparamagnetic clustering algorithm. Our experiments
show that depth gradients are more useful than depth values for segmentation,
and that channel coding both colour and depth gradients makes
tuned parameter settings generalise better to novel images.
CitationWallenberg, M. [et al.]. Channel coding for joint colour and depth segmentation. A: Annual Symposium of the German Association for Pattern Recognition. "2011 Annual Symposium of the German Association for Pattern Recognition". Frankfurt: Springer, 2011, p. 306-315.
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