Commercial photogrammetry software packages have been extensively validated for
accident reconstruction applications, and these software packages are widely
used to measure physical evidence such as roadway evidence, vehicle crush
profiles, and vehicle speeds from videos. While effective, these tools rely on
proprietary licenses and subscription models that can pose financial barriers
for some users, particularly law-enforcement agencies and smaller institutions.
Blender, using the CamMatch add-on, is used to solve camera intrinsics,
including lens distortion parameters, as well as the camera position and
orientation for reverse-projection photogrammetry workflows. CamMatch generates
a virtual camera that is correctly positioned and oriented within the 3D scene,
which is then used to overlay the undistorted video directly onto the scene.
This alignment enables reverse-projection analysis from which vehicle position
and speed can be determined. Data from SAE Paper 2025-01-8700 was used, where
vehicle speeds were calculated by utilizing the footage recorded by front, left
repeater, right repeater, and back cameras of Tesla Model 3 and Tesla Model Y
vehicles. In the reference study, GPS-instrumented target vehicles equipped with
Racelogic VBOX systems traveled across each camera’s field of view at speeds
ranging from 7.2 km/h to 20.4 km/h. Video footage was retrieved via direct USB
download from the subject Tesla vehicles. Our study utilized reverse-projection
photogrammetry with Blender, using cameras generated by CamMatch with point
cloud representations of both the test environments and target vehicles used to
establish 3D reference geometry. Vehicle speeds determined from this process
exhibited an error (mean ± SD) of 1.84 ± 1.15% across 25
tests compared to an error of 2.10 ± 1.63% calculated in
PhotoModeler. Moreover, the maximum difference between the VBOX data and the
calculated speeds among all the results was found to be 0.53 kph.
These findings support the use of CamMatch as an open-source tool for
photogrammetry with capabilities comparable to the established photogrammetry
methodologies.