Image based automatic vehicle damage detection

This thesis describes research undertaken to address the problem of automatic vehicle damage detection using photographs. A pipeline addressing a vertical slice of the broad problem is considered while focusing on mild vehicle damage detection. We propose to use 3D CAD models of undamaged vehicles which are used to obtain ground truth information in order to infer what the vehicle with mild damage in the photograph should have looked like, if it had not been damaged. To this end, we develop 3D pose estimation algorithms to register an undamaged 3D CAD model over a photograph of the known dam- aged vehicle. We present a 3D pose estimation method using image gradient information of the photograph and the 3D model projection. We show how the 3D model projection at the recovered 3D pose can be used to identify components of a vehicle in the photograph which may have mild damage. In addition, we present a more robust 3D pose estimation method by minimizing a novel illumination invariant distance measure, which is based on a Mahalanobis distance between attributes of the 3D model projection and the pixels in the photograph. In principle, image edges which are not present in the 3D CAD model projection can be considered to be vehicle damage. The performance of the proposed methods are experimentally evaluated on real photographs using 3D CAD models of varying accuracy. We expect that the research presented in this thesis will provide the groundwork for designing an automatic photograph based vehicle damage detection system. Moreover, we hope that our method will provide the foundation for interesting future research.


  • English

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  • Pagination: 1 file

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Filing Info

  • Accession Number: 01534331
  • Record Type: Publication
  • Source Agency: ARRB
  • Files: ITRD, ATRI
  • Created Date: Aug 11 2014 2:46PM