An algorithm to estimate velocity fields from low-resolution video recordings is presented. The algorithm does not attempt to identify and track individual vehicles, nor does it attempt to estimate derivatives of the field of pixel intensities. Rather, a frame is compressed by obtaining an intensity profile in each lane along the direction of traffic flow. The speed estimate is then computed by searching for a best matching profile in a frame at earlier and later times. It is shown that the estimate is equivalent to a weighted median of velocities of vehicles. Because the algorithm does not need high-quality images, it is directly applicable to a compressed format digital video stream, such as .mpeg, from conventional traffic video cameras. The procedure is illustrated using a 15-min-long Video Home System recording to obtain speed estimates on a 1-mi stretch of highway I-80 in Berkeley, CA
['Young H. Cho', 'John Rice']
Estimating Velocity Fields on a Freeway From Low-Resolution Videos