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Detecting Road Users at Intersections Through Changing Weather Using RGB-Thermal Video

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Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

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Abstract

This paper compares the performance of a watch-dog system that detects road user actions in urban intersections to a KLT-based tracking system used in traffic surveillance. The two approaches are evaluated on 16 h of video data captured by RGB and thermal cameras under challenging light and weather conditions. On this dataset, the detection performance of right turning vehicles, left turning vehicles, and straight going cyclists are evaluated. Results from both systems show good performance when detecting turning vehicles with a precision of 0.90 and above depending on environmental conditions. The detection performance of cyclists shows that further work on both systems is needed in order to obtain acceptable recall rates.

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Acknowledgements

The authors thank Tanja Kidmann Osmann Madsen for acquiring the data as well as assistance on the ground truth. This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No. 635895. This publication reflects only the author’s view. The European Commission is not responsible for any use that may be made of the information it contains.

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Authors and Affiliations

  1. Visual Analysis of People Laboratory, Aalborg University, Aalborg, Denmark

    Chris Bahnsen & Thomas B. Moeslund

Authors
  1. Chris Bahnsen
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  2. Thomas B. Moeslund
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Corresponding author

Correspondence to Chris Bahnsen .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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Bahnsen, C., Moeslund, T.B. (2015). Detecting Road Users at Intersections Through Changing Weather Using RGB-Thermal Video. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_66

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  • DOI: https://doi.org/10.1007/978-3-319-27857-5_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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