Application of Interactive Video Sensing and Management for Pedestrian and Bicycle Safety Studies

Wu-chi Feng, Portland State University



As video data collection and storage technologies become ubiquitous and inexpensive, transportation agencies struggle to process and extract "intelligence" or useful information from growing libraries of archived video data. In some cases useful video is lost because agencies cannot justify the expensive staff time required to process it. This video information overload is caused by the inability of most transportation agencies to write customized video processing algorithms to extract valuable safety or traffic data from large amounts of collected raw video. 

Manually watching long stretches of video to extract information is boring and expensive. In addition to being time and financially inefficient, human-based extraction of video data is prone to errors. Although there are some sophisticated, specialized applications for transportation agencies these are either/both proprietary or/and too expensive to be widely deployed.

In this project, we designed and implemented a user-friendly interface for pedestrian crossing and vehicle conflict detection, leveraging the OpenCV computer-vision libraries made available via open-source from Intel. The goal is to allow practitioners to more easily provide the semantics of the information they wish to extract and process into the video-processing algorithms. As a demonstration and development tool, we used a complicated mid-block crosswalk located on Southwest 4th Avenue. This is a busy downtown street on the Portland State University (PSU) campus. There are three lanes of heavy one-way motor vehicle traffic; speeds are moderate as most vehicles have just exited Interstate 405 (I-405). We used this location to demonstrate how easily and accurately our flexible, user-friendly tool can measure pedestrian wait times, crossing speeds, and near misses (e.g., a car abruptly stopping prior to the crosswalk or a vehicle passing a stopped vehicle). In addition, the system outputs meaningful data about vehicle and pedestrian trajectories for further analysis.


The goal of the project is to create an interactive, video sensor system which will combine computer vision techniques into a user friendly interface that can be easily “programmed” and adjusted by the researchers to study some of the most frequent traffic safety issues such as vehicle and pedestrian conflicts in the time-space plane or bicycle compliance with traffic signals.    The main impact will be the ability to automatically process pedestrian and vehicular traffic without (i) very complex and non-extensible software algorithms and (ii) to allow users to provide basic input into the computer vision process.

Project Details

Project Type:
Project Status:
End Date:
June 30,2014
UTC Grant Cycle:
Tier 1 Round 1
UTC Funding:

Other Products

  • Addressing the Semantic Gap Between Video Sensors and Applications (PRESENTATION)