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Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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Vehicle Orientation Detection Using CNN

  • Nguyen, Huu Thang (School of Electronic and Electrical Engineering, Hongik University) ;
  • Kim, Jaemin (School of Electronic and Electrical Engineering, Hongik University)
  • Received : 2021.11.24
  • Accepted : 2021.12.06
  • Published : 2021.12.31
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Abstract

Vehicle orientation detection is a challenging task because the orientations of vehicles can vary in a wide range in captured images. The existing methods for oriented vehicle detection require too much computation time to be applied to a real-time system. We propose Rotate YOLO, which has a set of anchor boxes with multiple scales, ratios, and angles to predict bounding boxes. For estimating the orientation angle, we applied angle-related IoU with CIoU loss to solve the underivable problem from the calculation of SkewIoU. Evaluation results on three public datasets DLR Munich, VEDAI and UCAS-AOD demonstrate the efficiency of our approach.

Keywords

Acknowledgement

This work was supported by Hongik University Research Fund.

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