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Rollover crashes are complex events that generate motions in all six degrees of freedom (6DOF). Directly quantifying the angular rotations from video can be difficult and vehicle orientation as a function of time is often not reported for staged rollover crashes. Our goal was to evaluate the ability of using a match-moving technique and consumer-grade video cameras to quantify the roll, pitch and yaw angles and angular velocities of a rollover crash. We staged a steer-induced rollover of an SUV at 106 km/h. The vehicle was fitted with tri-axial accelerometers and angular rate sensors, and five consumer-grade video cameras (2 on tripods, 2 on drones, 1 handheld, ~30 fps) captured the event. Roll, pitch and yaw angles were determined from the video using specialized software.

Estimation of target-to-background luminance ratios is a powerful method by which human detection of objects can be assessed. In the forensic community, evaluation of the detectability of a pedestrian to an automobile driver is often of interest. With calibration, the modern digital camera employing a CCD or CMOS light collection device can be a convenient and economical luminance estimation tool. Certain CCD or CMOS sensors will linearly report the impinging incident light pixel by pixel over a range of intensities. The device becomes nonlinear at low and high intensities; however, the linear region can be adjusted to the specific lighting conditions of interest by modifying the shutter speed, ISO setting, and aperture size. Image noise, sensor non-uniformity, temperature sensitivity, camera color sensitivity, and the spectral power distribution of the illuminant require treatment for direct comparison to the luminance.