University of Washington Bi-directional traffic flow parameters estimation from aerial videos - An application of unmanned aerial vehicle PacTrans STAR Lab University of Washington July 17, 2015 Ruimin Ke Email: ker27@uw.edu

Motivation Low operating cost Large monitoring area Emergency response

Application Traffic monitoring Law enforcement Precision Farming Firefighting Assistance in flooding efforts Customs and Border patrol Making drug bust Amazon delivery service 3D model creation

Application in Traffic Monitoring Road detection Incident detection Vehicle detection and tracking Traffic parameters estimation Pedestrian and cyclists detection and tracking

Challenge Privacy issue Moving background & Moving foreground

Objective Automatically extracting traffic flow parameters in real time - Speed - Density - Flow

Methodology Track feature points: Motion-vector clustering Kanade-Lucas-Tomasi optical flow tracker Motion-vector clustering K-means clustering Multi-vehicle detection and counting Connected graph Traffic parameters determination Using reference marks

Thanks for your attention!   Ruimin Ke ker27@uw.edu