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A State of the Art Report on Kinect Sensor Setups in Computer Vision

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Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8200))

Abstract

During the last three years after the launch of the Microsoft Kinect® in the end-consumer market we have become witnesses of a small revolution in computer vision research towards the use of a standardized consumer-grade RGBD sensor for scene content retrieval. Beside classical localization and motion capturing tasks the Kinect has successfully been employed for the reconstruction of opaque and transparent objects. This report gives a comprehensive overview over the main publications using the Microsoft Kinect out of its original context as a decision-forest based motion-capturing tool.

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Authors and Affiliations

  1. OeRC Oxford, University of Oxford, UK

    Kai Berger

  2. Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

    Stephan Meister, Rahul Nair & Daniel Kondermann

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  1. Kai Berger
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  1. Pattern Recognition Group, University of Siegen, Siegen, Germany

    Marcin Grzegorzek

  2. Max-lanck-Institute, Graphics, Vision & Video Gruop, Saarbrücken, Germany

    Christian Theobalt

  3. Multimedia Information Processing Group, University of Kiel, Kiel, Germany

    Reinhard Koch

  4. Computer Graphics and Multimedia Systems Group, University of Siegen, Siegen, Germany

    Andreas Kolb

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Berger, K., Meister, S., Nair, R., Kondermann, D. (2013). A State of the Art Report on Kinect Sensor Setups in Computer Vision. In: Grzegorzek, M., Theobalt, C., Koch, R., Kolb, A. (eds) Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications. Lecture Notes in Computer Science, vol 8200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44964-2_12

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