In this study, we make use of a stereo photogrammetric data set, which was collected during T-REX but little used thus far. Using photogrammetric data is a little known but highly valuable tool for studying smaller, highly ephemeral clouds. The T-REX data set consists of matched stereo pairs of photographic images obtained at high temporal (on the order of seconds) and spatial resolution (limited by the pixel size of the cameras). To this data set, we have applied computer vision techniques to develop algorithms for camera calibration, automatic feature matching, and ultimately reconstruction of 3D cloud scenes. Using the photogrammetric imagery, we have been able to track the 3D path of cloud fragments at the upstream edge of the rotor cloud and monitor their growth and dynamics until their merger with the main cloud. The excellent temporal and spatial resolution of the images allows us to demonstrate the existence of small-scale features in the highly turbulent airflow at the leading edge of rotors and quantify their spatial and temporal scales.