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Ground-Truth Tracking Data Generation Using Rotating Real-World Objects

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 693))

Abstract

Quantitative comparison of feature matchers/trackers is essential in 3D computer vision as the accuracy of spatial algorithms mainly depends on the quality of feature matching. This paper shows how a structured-light applying turntable-based evaluation system can be developed. The key problem here is the highly accurate calibration of scanner components. The ground truth (GT) tracking data generation is carried out for seven testing objects. It is shown how the OpenCV3 feature matchers can be compared on our GT data, and the obtained quantitative results are also discussed in detail.

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Notes

  1. 1.

    http://vision.middlebury.edu/.

  2. 2.

    These arms are can also move, but their calibration is not considered here, it is a possible future work.

  3. 3.

    The BRIEF descriptor is not invariant to rotation, however, we hold it in the set of testing algorithms as it surprisingly served good results.

  4. 4.

    OpenCV’s documentation is not very informative about Hamming2 distance. They suggest the usage of that for ORB features. However, it can be applied for other possible descriptors, therefore all possible combinations are tried in our tests.

  5. 5.

    Many researchers have informed us that the OpenCV MSER implementation is not perfect.

  6. 6.

    Feature track length is defined as the number of images on which the feature appears.

  7. 7.

    http://web.eee.sztaki.hu.

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Acknowledgement

This work was partially supported by the Hungarian National Research, Development and Innovation Office under the grant VKSZ_14-1-2015-0072.

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Authors and Affiliations

  1. Distributed Events Analysis Research Laboratory, MTA SZTAKI, Kende utca 13-17, Budapest, 1111, Hungary

    Zoltán Pusztai & Levente Hajder

  2. Eötvös Loránd University, Budapest, Hungary

    Zoltán Pusztai & Levente Hajder

Authors
  1. Zoltán Pusztai
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  2. Levente Hajder
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Correspondence to Levente Hajder .

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Editors and Affiliations

  1. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

  2. MiraLab, University of Geneva, Carouge, Switzerland

    Nadia Magnenat-Thalmann

  3. LISA - ISTIA, University of Angers, Angers, France

    Paul Richard

  4. Department of Computer Science and Electrical Engineering, Jacobs University, Bremen, Germany

    Lars Linsen

  5. University of Groningen, Groningen, The Netherlands

    Alexandru Telea

  6. Università di Catania, Catania, Italy

    Sebastiano Battiato

  7. Research Innovation Center, Canon U.S.A. Inc., San Jose, California, USA

    Francisco Imai

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Pusztai, Z., Hajder, L. (2017). Ground-Truth Tracking Data Generation Using Rotating Real-World Objects. In: Braz, J., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2016. Communications in Computer and Information Science, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-64870-5_19

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