Detection and classification of vehicles from omnidirectional videos using multiple silhouettes

@article{Karaimer2017DetectionAC,
  title={Detection and classification of vehicles from omnidirectional videos using multiple silhouettes},
  author={Hakki Can Karaimer and I. Baris Schlicht and Yalin Bastanlar},
  journal={Pattern Analysis and Applications},
  year={2017},
  volume={20},
  pages={893-905}
}
To detect and classify vehicles in omnidirectional videos, we propose an approach based on the shape (silhouette) of the moving object obtained by background subtraction. Different from other shape-based classification techniques, we exploit the information available in multiple frames of the video. We investigated two different approaches for this purpose. One is combining silhouettes extracted from a sequence of frames to create an average silhouette, the other is making individual decisions… 
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