Video and photo based photogrammetry software has many applications in the accident reconstruction community including documentation of vehicles and scene evidence. Photogrammetry software has developed in its ease of use, cost, and effectiveness in determining three dimensional data points from two dimensional photographs. Contemporary photogrammetry software packages offer an automated solution capable of generating dense point clouds with millions of 3D data points from multiple images. While alternative modern documentation methods exist, including LiDAR technologies such as 3D scanning, which provide the ability to collect millions of highly accurate points in just a few minutes, the appeal of automated photogrammetry software as a tool for collecting dimensional data is the minimal equipment, equipment costs and ease of use. This paper evaluates the accuracy and capabilities of four automated photogrammetry based software programs to accurately create 3D point clouds, by comparing the results to 3D scanning. Both a damaged and undamaged vehicle were documented with video and photographs and on average the damaged vehicle set returned more data points with higher accuracy than the undamaged vehicle set. Four cameras types were evaluated and more accurate results were achieved when using either a DSLR or a point-and-shoot camera than when using a GoPro, or a cell phone camera. Photogrammetry data from video footage was analyzed and found to be both less accurate and to return less data than photographs. By limiting the number of photographs used, it was found that a photogrammetry solution could be achieved with as few as 16 photographs encircling a vehicle, but better results were reached with a larger number of photographs.