Front-View Vehicle Damage Detection using Roadway Surveillance Camera Images

Burak Balci, Yusuf Artan, Bensu Alkan, Alperen Elihos

2019

Abstract

Vehicle body damage detection from still images has received considerable interest in the computer vision community in recent years. Existing methods are typically developed towards the auto insurance industry to minimize the claim leakage problem. Earlier studies utilized images taken from short proximity (< 3 meters) to the vehicle or to the damaged region of vehicle. In this study, we investigate the vehicle frontal body damage detection using roadway surveillance camera images. The proposed method utilizes deep learning based object detection and image classification methods to determine damage status of a vehicle. The proposed method combines the symmetry property of vehicles’ frontal view and transfer learning concept in its inference process. Experimental results show that the proposed method achieves 91 % accuracy on a test dataset.

Paper Citation

in Harvard Style

Balci B., Artan Y., Alkan B. and Elihos A. (2019). Front-View Vehicle Damage Detection using Roadway Surveillance Camera Images .In Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-374-2, pages 193-198. DOI: 10.5220/0007724601930198

in Bibtex Style

@conference{vehits19,
author={Burak Balci and Yusuf Artan and Bensu Alkan and Alperen Elihos},
title={Front-View Vehicle Damage Detection using Roadway Surveillance Camera Images },
booktitle={Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2019},
pages={193-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007724601930198},
isbn={978-989-758-374-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Front-View Vehicle Damage Detection using Roadway Surveillance Camera Images
SN - 978-989-758-374-2
AU - Balci B.
AU - Artan Y.
AU - Alkan B.
AU - Elihos A.
PY - 2019
SP - 193
EP - 198
DO - 10.5220/0007724601930198