Abstract
In this paper, we present our work on GPU-based real-time extraction of surface patches by means of Kinect cameras. This paper makes four contributions: (1) we derive an uncertainty model for pixel-wise depth reconstruction on Kinect cameras; (2) we implement a real-time algorithm for surface patch (here called ‘texlet’) extraction based on Kinect depth data on a GPU. For that we compare and evaluate different implementation alternatives. (3) Based on (1) we derive and implement an appropriate uncertainty model for texlets which is also computed in real-time. (4) We investigate and quantify the effect of interferences on the depth extraction process when using multiple Kinect cameras. By these contributions we present insights into the processing of depth and how to achieve higher precision reconstructions by means of Kinect cameras as well as extend their use for higher level visual processing. The introduced algorithms are available in the C++ vision library CoViS.
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Notes
See e.g., the LibFreenect driver http://openkinect.org.
Point Cloud Library, http://pointclouds.org.
Robot Operating System, http://www.ros.org.
see e.g., CULA tools (http://culatools.com).
Some of the solutions might be coinciding or zero.
Some points in a neighborhood might be discarded as a result of outlier rejection.
This is similar to the Unscented Transform method [10].
If only one or two Kinects were used, it would not be possible to get all relations, due to an incomplete scene representation.
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This work has been supported by the IntellAct project (FP7-ICT-269959).
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Olesen, S.M., Lyder, S., Kraft, D. et al. Real-time extraction of surface patches with associated uncertainties by means of Kinect cameras. J Real-Time Image Proc 10, 105–118 (2015). https://doi.org/10.1007/s11554-012-0261-x
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DOI: https://doi.org/10.1007/s11554-012-0261-x