Abstract
Vehicle headlights are the important objects especially in the application of night-time traffic surveillance. A common problem of this task is the similarity between the headlights and their reflections on the road. This paper proposes a novel algorithm to construct 3D motion trajectories of headlights and their reflections on the road using both spatial and temporal information. 3D structure tensors are utilized as shape features for recognizing the headlights in various traffic views. Experimental results show that the proposed method performs better than traditional approaches (about 10 \(\%\)) in terms of the F1 score.
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Acknowledgements
This research is financially supported by the National Science and Technology Development Agency (NSTDA), National Research University Project, Thailand Office of the Higher Education Commission, Japan Advanced Institute of Technology (JAIST), and Thammasat University Research Fund under the TU Research Scholar, Contract No. 27/2561. The traffic video dataset is partly supported by the National Science Foundation under Grant No. CCF-1319800.
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Sooksatra, S., Kondo, T., Bunnun, P. et al. Headlight recognition for night-time traffic surveillance using spatial–temporal information. SIViP 14, 107–114 (2020). https://doi.org/10.1007/s11760-019-01530-4
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DOI: https://doi.org/10.1007/s11760-019-01530-4