A Multiple Hypothesis Approach for a Ball Tracking System
Oliver Birbach and Udo Frese
In Proceedings of the 7th International Conference on Computer Vision Systems, ICVS 2009. Liege, Belgium, October 13-15, 2009.
Abstract: This paper presents a computer vision system for tracking and predicting flying balls in 3-D from a stereo-camera. It pursues a textbook-style approach with a robust circle detector and probabilistic models for ball motion and circle detection handled by state-of-the-art estimation algorithms. In particular we use a Multiple-Hypotheses Tracker (MHT) with an Unscented Kalman Filter (UKF) for each track, handling multiple flying balls, missing and false detections and track initiation and termination.
The system also performs auto-calibration estimating physical parameters (ball radius, gravity relative to camera, air drag) simply from observing some flying balls. This reduces the setup time in a new environment.
Example frames from the tracking results:
Video: The video mentioned in the paper can be downloaded here.