Video-based vehicle speed estimation from motion vectors in video streams

摘要

Automated low-complexity video-based vehicle speed estimation is described, that operates within the video stream to screen video sequences to identify and eliminate clear non-violators and/or identify and select potential violators within a multi-layer speed enforcement system, in which deeper layers provide enhanced accuracy on selected candidate (speeding) vehicles. Video motion vector clusters corresponding to a vehicle are identified and tracked across multiple frames of captured video. Movement of the motion vector clusters translated from pixels per second to real speed (e.g. miles per hour) to determine whether the vehicle was speeding. Estimated speed data is added to the video stream data is metadata, and video segments of candidate speeding vehicles are stored and/or transmitted for subsequent review (e.g. automated or manual).