Robust tracking of people in crowds with covariance descriptors

Jürgen Metzler; Dieter Willersinn

doi:10.1117/12.820067

27 April 2009 Robust tracking of people in crowds with covariance descriptors

Jürgen Metzler, Dieter Willersinn

Proceedings Volume 7341, Visual Information Processing XVIII; 73410T (2009) https://doi.org/10.1117/12.820067
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

In order to control riots in crowds, it is helpful to get the ringleader under control. A great support to achieve this task is the capability to automatically track individual persons in a video sequence taken from a crowd. In this paper we address the robustness of such a tracking function. We start from the results of a previous evaluation of tracking methods, where a so-called Covariance-Tracker was found to be most appropriate. This tracker uses covariance matrices as object descriptors, as proposed by Porikli et al. The set of all covariance matrices describes a Riemannian manifold that is used to compare and update the covariance descriptors during tracking. We propose Covariance-Tracker adaptations to improve its performance. Furthermore, we summarize the performance evaluation results of the original method and compare these with the results of the adapted one. The result is a robust method for tracking people in crowds which can improve situational awareness.

Citation Download Citation

Jürgen Metzler and Dieter Willersinn "Robust tracking of people in crowds with covariance descriptors", Proc. SPIE 7341, Visual Information Processing XVIII, 73410T (27 April 2009); https://doi.org/10.1117/12.820067

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