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Photogrammetry is a commonly used and accepted technique within the field of accident reconstruction for taking measurements from photographs. Previous work has shown the accuracy of optimized close-range photogrammetry techniques to be within 2 mm compared to other high accuracy measurement techniques when using a known calibrated camera. This research focuses on the use of inverse camera close-range photogrammetry, where photographs from an unknown camera are used to model a vehicle. Photogrammetry is a measurement technique that utilizes triangulation to take measurements from photographs. The measurements are dependent on the geometry of the camera, such as the sensor size, focal length, lens type, etc. Three types of cameras were tested for accuracy; a high-end commercial camera, a point and shoot camera, and a cell phone camera.

Understanding the specific illumination pattern of a vehicle headlamp beam is useful for the evaluation of nighttime visibility issues in accident reconstruction. There are several challenges associated with traditional headlamp mapping techniques, including that mapping must be conducted in darkness, the mapping location topography may not be level or flat, maintaining a measurement grid is difficult to accomplish in the field, data acquisition requires multiple individuals, and it is generally very time consuming. Traditional techniques require the surrounding surface to be permanently marked in the evening in order to allow for future data collection of the mapped points in daylight conditions. The methodology presented here alleviates some of these challenges through real-time data collection and by accounting for topographical differences, which eliminates the requirement that mapping be conducted on a level or flat surface, and it reduces the number of required participants.