A graphical interface for semi-automated road user tracking

Although tracking moving objects in video data is more and more common in many applications, for example for surveillance and transportation, no algorithm can perform perfectly in all real world conditions, because of crowding, mixed traffic, varying lighting and weather conditions, etc. In applied fields such as transportation, the quality of the output data is critical, in particular for specific event detection. It is therefore interesting to be able to quickly review tracking results and correct them for subsequent analysis.

The goal of this project is to develop a graphical user interface (GUI) to visualize the results of a tracker applied to road traffic, review the quality of the trajectories and correct them as efficiently (with as little manual user input) as possible. An open source feature-based tracking tool has been developed in our research group (http://bitbucket.org/Nicolas/trafficintelligence) and will produce the results to be reviewed and cleaned in the tool. Tests will be conducted on real world datasets. An extension of the work will be to learn typical tracking errors to automatically identify tracker errors and event correct them automatically.

Faculty Supervisor:

Nicolas Saunier

Student:

Akhil Vakayil

Partner:

Discipline:

Engineering - civil

Sector:

University:

Program:

Globalink