Applying Camera Matching Methods to Laser Scanned Three Dimensional Scene Data with Comparisons to Other Methods 2015-01-1416

In the field of accident reconstruction, a reconstructionist will often inspect a crash scene months or years after a crash has occurred. With this passage of time important evidence is sometimes no longer present at the scene (i.e. the vehicles involved in the crash, debris on the roadway, tire marks, gouges, paint marks, etc.). When a scene has not been totally documented with a survey by MAIT or the investigating officers, the reconstructionist may need to rely on police, fire department, security camera, or witness photographs. These photos can be used to locate missing evidence by employing traditional photogrammetric techniques. However, traditional techniques require planar surfaces, matched discrete points, or camera matching at the scene. Sometimes it is not possible to survey discrete points or perform camera matching at the scene due to lack of access (the tops of power poles, elevated bridge features, or objects at a great distance) or for safety reasons (interstate highways with high traffic conditions or on narrow bridges). Other times important evidence can be located on a hill or depressed median and planar photogrammetric methods are not effective. In recent years three dimensional laser scanners have been utilized by accident investigators allowing the reconstructionist to document a crash scene with millions of points in minutes so that a “point cloud” can be created. The equipment is fast, simple to setup, and is very accurate, thus allowing the reconstructionist the ability to take home a three dimensional model of the scene for in depth analysis.

This paper will describe the scanning equipment, photo considerations, and a methodology for utilizing three dimensional laser scan data and camera matching to extract evidence from first responder photographs or videos. The accuracies of this technique are compared to other accepted methods such as planar photogrammetry, Discrete Point Software, and photo rectification over point cloud data.

The camera matching method of locating evidence has been described in literature before [1,2,7] but technology advances have allowed the method to be expanded upon. The camera matching method now applied to a three dimensional point cloud with millions of points used for the solution allows easy and accurate extraction of evidence on not only flat areas but complex terrains as well. A simulated crash which is called a “staged collision” is analyzed. This “staged collision” represents two types of evidence. One type of evidence is on a flat surface to compare planar accuracies. The second type of evidence is in an area incorporating large changes in the terrain to compare three dimensional accuracies. Various photogrammetry methods are compared in these two types of terrain and it is shown how combining laser scan data with the “virtual camera matching to point cloud” technique can accurately extract evidence from non-planar areas with large changes in terrain.