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Videogrammetry in Vehicle Crash Reconstruction with a Moving Video Camera
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
In an accident reconstruction, vehicle speeds and positions are always of interest. When provided with scene photographs or fixed-location video surveillance footage of the crash itself, close-range photogrammetry methods can be useful in locating physical evidence and determining vehicle speeds and locations. Available 3D modeling software can be used to virtually match photographs or fixed-location video surveillance footage. Dash- or vehicle-mounted camera systems are increasingly being used in light vehicles, commercial vehicles and locomotives. Suppose video footage from a dash camera mounted to one of the vehicles involved in the accident is provided for an accident reconstruction but EDR data is unavailable for either of the vehicles involved. The literature to date describes using still photos to locate fixed objects, using video taken from stationary camera locations to determine the speed of moving objects or using video taken from a moving vehicle to locate fixed objects. However, techniques to evaluate the position, speed and acceleration of moving objects seen in video taken from moving locations have not been evaluated. To address the increasing prevalence of dash cams and other in-vehicle video and the value in using such video in vehicle crash reconstruction, this paper describes techniques for determining the position and speed of a moving object from digital video taken from a moving vehicle. Evaluations of the accuracy of those techniques were done when provided three different levels of information about the environment:
- 1Aerial Photography (USGS)
- 2Survey Data (Total Station)
- 33D Scan Data (of both the environment and vehicles)
CitationManuel, E., Mink, R., and Kruger, D., "Videogrammetry in Vehicle Crash Reconstruction with a Moving Video Camera," SAE Technical Paper 2018-01-0532, 2018, https://doi.org/10.4271/2018-01-0532.
Data Sets - Support Documents
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