Cameras and crowds in transportation tracking

Abstract

Active transportation is an important contributor to physical activity. Understanding active transportation trends and transportation mode share is important to public health research and city planners. Objective measurement of active transportation can be costly and time-consuming, and existing camera-based algorithms, while developing, are functionally limited to specific settings and distances. In this study, 28,992 publicly available webcam images from two intersections in Washington, D.C., were used to establish trends in active transportation. Amazon Mechanical Turk workers were found to be reliable identifiers of pedestrian and vehicular activity, data validated against trained research assistant image annotation. Webcam and crowdsource annotation provides a cost-effective alternative to traditional objective measures of active transportation and mode share through the use of publicly available wireless webcams. Additional research is needed to expand the utility and external validity of publicly available imaged-based active transportation methodology and image annotation.