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Efficient Multi-frequency Phase Unwrapping Using Kernel Density Estimation
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5698-5983
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
2016 (English)In: Computer Vision – ECCV 2016 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part IV / [ed] Bastian Leibe, Jiri MatasNicu Sebe and Max Welling, Springer, 2016, p. 170-185Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we introduce an efficient method to unwrap multi-frequency phase estimates for time-of-flight ranging. The algorithm generates multiple depth hypotheses and uses a spatial kernel density estimate (KDE) to rank them. The confidence produced by the KDE is also an effective means to detect outliers. We also introduce a new closed-form expression for phase noise prediction, that better fits real data. The method is applied to depth decoding for the Kinect v2 sensor, and compared to the Microsoft Kinect SDK and to the open source driver libfreenect2. The intended Kinect v2 use case is scenes with less than 8m range, and for such cases we observe consistent improvements, while maintaining real-time performance. When extending the depth range to the maximal value of 18.75 m, we get about 52% more valid measurements than libfreenect2. The effect is that the sensor can now be used in large depth scenes, where it was previously not a good choice.

Place, publisher, year, edition, pages
Springer, 2016. p. 170-185
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9908
Keywords [en]
Time-of-flight; Kinect v2; Kernel-density-estimation
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-133549DOI: 10.1007/978-3-319-46493-0_11ISI: 000389385100011ISBN: 9783319464923 (print)ISBN: 9783319464930 (electronic)OAI: oai:DiVA.org:liu-133549DiVA, id: diva2:1060849
Conference
14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part IV
Available from: 2016-12-30 Created: 2016-12-29 Last updated: 2018-10-10Bibliographically approved

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Järemo-Lawin, FelixForssén, Per-ErikOvrén, Hannes
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