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Ground truth annotation of traffic video data

Multimedia Tools and Applications volume 70, pages 461–474 (2014)Cite this article

Abstract

This paper presents a software application to generate ground-truth data on video files from traffic surveillance cameras used for Intelligent Transportation Systems (IT systems). The computer vision system to be evaluated counts the number of vehicles that cross a line per time unit –intensity-, the average speed and the occupancy. The main goal of the visual interface presented in this paper is to be easy to use without the requirement of any specific hardware. It is based on a standard laptop or desktop computer and a Jog shuttle wheel. The setup is efficient and comfortable because one hand of the annotating person is almost all the time on the space key of the keyboard while the other hand is on the jog shuttle wheel. The mean time required to annotate a video file ranges from 1 to 5 times its duration (per lane) depending on the content. Compared to general purpose annotation tool a time factor gain of about 7 times is achieved.

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Acknowledgments

The authors thank Etra I+D and Ruth López and Jaime Benlloch from Local Traffic Authority of Valencia, Spain by providing the video files. Also thanks to the VIGTA 2012 Conference Organizers, its participants and the anonymous reviewers of this journal for their valuable advice.

This work was funded by the Spanish Government project MARTA under the CENIT program and CICYT contract TEC2009-09146.

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Authors and Affiliations

  1. ITeam, Universitat Politècnica de València, Valencia, Spain

    Jose M. Mossi, Antonio Albiol, Alberto Albiol & Javier Oliver

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  1. Jose M. Mossi
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  2. Antonio Albiol
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  3. Alberto Albiol
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  4. Javier Oliver
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Correspondence to Jose M. Mossi.

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Mossi, J.M., Albiol, A., Albiol, A. et al. Ground truth annotation of traffic video data. Multimed Tools Appl 70, 461–474 (2014). https://doi.org/10.1007/s11042-013-1396-x

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  • DOI: https://doi.org/10.1007/s11042-013-1396-x

Keywords

  • Traffic
  • Ground truth
  • Vehicle
  • Video
  • Intelligent transportation systems