Photo-based automatic 3D reconstruction of train accident scenes

This data was imported from Scopus:

Authors: Tang, Z., Nie, Y., Chang, J., Zhang, J. and Liu, F.

http://eprints.bournemouth.ac.uk/30290/

Journal: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit

Volume: 232

Issue: 1

Pages: 144-158

eISSN: 2041-3017

ISSN: 0954-4097

DOI: 10.1177/0954409716662089

© 2016, © IMechE 2016. Railway accidents place significant demands on the resources of, and support from, railway emergency management departments. Once an accident occurs, an efficient incident rescue plan needs to be delivered as early as possible to minimise the loss of life and property. However, in the railway sector, most relevant departments currently face a challenge in drawing up a rescue scheme effectively and accurately with the insufficient information collected from the scene of a train accident. To assist with the rescue planning, we propose a framework which can rapidly and automatically construct a 3D virtual scene of a train accident by utilising photos of the accident spot. The framework uses a hybrid 3D reconstruction method to extract the position and pose information of the carriages involved in an accident. It adopts a geographic information system and a 3D visualisation engine to model and display the landscapes and buildings at the site of a train accident. In order to assess and validate our prototype, we quantitatively evaluate our main algorithm and demonstrate the usage of our technology with two case studies including a simulated scene with an in-lab setting and a real train derailment scene from on-site pictures. The results of both are accountable with high accuracy and represent the ability of timely modelling and visualisation of a train accident scene.

This data was imported from Web of Science (Lite):

Authors: Tang, Z., Nie, Y., Chang, J., Zhang, J. and Liu, F.

http://eprints.bournemouth.ac.uk/30290/

Journal: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT

Volume: 232

Issue: 1

Pages: 144-158

eISSN: 2041-3017

ISSN: 0954-4097

DOI: 10.1177/0954409716662089

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