Abstract
The use of multiple Microsoft Kinect has become prominent in the last 2 years and enjoyed widespread acceptance. While several work has been published to mitigate quality degradations in the precomputed depth image, this work focuses on employing an optical flow suitable for dot patterns as employed in the Kinect to retrieve subtle scene data alterations for reconstruction. The method is employed in a multiple Kinect vision architecture to detect the interface of propane flow around occluding objects in air.
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Acknowledgments
Supplementary Videos are accessible under https://dl.dropbox.com/u/21912442/supplementary.zip. The authors would like to thank Manuel Martinez from KIT, Karlsruhe, who helped with generating synthetic depth images from the spot pattern images.
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Berger, K., Kastner, M., Schroeder, Y., Guthe, S. (2014). Using Sparse Optical Flow for Two-Phase Gas Flow Capturing with Multiple Kinect. In: Shao, L., Han, J., Kohli, P., Zhang, Z. (eds) Computer Vision and Machine Learning with RGB-D Sensors. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-08651-4_8
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DOI: https://doi.org/10.1007/978-3-319-08651-4_8
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