Real-time multiple people tracking using competitive condensation

The Condensation algorithm has attracted attention as it has robust tracking performance and potential of real-time implementation. However the Condensation tracker has difficulty with real-time implementation for multiple people tracking since it requires complicated shape model and large number of samples for precise tracking performance. This paper presents two improvements for real-time multiple object tracking: the discrete shape model with a small search space and the competition rule which requires a small number of samples to track multiple people. We show that they achieve robust and real-time tracking for image sequences of a crowd of people.