The Placement of Digitized Objects in a Point Cloud as a Photogrammetric Technique

The frequency of video-capturing collision events from surveillance systems are increasing in reconstruction analyses. The video that has been provided to the investigator may not always include a clear perspective of the relevant area of interest. For example, surveillance video of an incident may have captured a pre- or post-incident perspective that, while failing to capture the precise moment when the pedestrian was struck by a vehicle, still contains valuable information that can be used to assist in reconstructing the incident. When surveillance video is received, a quick and efficient technique to place the subject object or objects into a three-dimensional environment with a known rate of error would add value to the investigation. In addition, once the objects have been placed into the three-dimensional environment, the investigator would then be able to observe the physical evidence and environment from any perspective, including viewing and measuring what cannot be seen in the video perspective. In this research, the proposed photogrammetric technique of visually placing objects within three-dimensional laser scans will be evaluated. This research aims to quantify the rate of error of taking measurements of these objects to known fixed reference points both in and out of view of the camera, and provide an efficient technique that can be employed by reconstructionists using only one software package. As a result of this research, the authors have developed an expedient, less time-intensive photogrammetric technique for the placement of three-dimensionally scanned objects and environments. This technique can take less than half of the time of a conventional photogrammetric solution.