Online Multi-Person Tracking by Tracker Hierarchy

Tracking-by-detection is a widely used paradigm for multi-person tracking but is affected by variations in crowd density, obstacles in the scene, varying illumination, human pose variation, scale changes, etc. We propose an improved tracking-by-detection framework for multi-person tracking where the appearance model is formulated as a template ensemble updated online given detections provided by a pedestrian detector. We employ a hierarchy of trackers to select the most effective tracking strategy and an algorithm to adapt the conditions for trackers' initialization and termination. Our formulation is online and does not require calibration information. In experiments with four pedestrian tracking benchmark datasets, our formulation attains accuracy that is comparable to, or better than, the state-of-the-art pedestrian trackers that must exploit calibration information and operate offline.

We provide source code and data for the tracker described in

Jianming Zhang, Liliana Lo Presti and Stan Sclaroff, "Online Multi-Person Tracking by Tracker Hierarchy," Proc. Int. Conf. on Advanced Video and Signal Based Surveillance (AVSS), 2012.

The source code is implemeted in C++.  A cmake file is included to help compile the code in windows and linux system. Please refer to the readme file for details. An implementation of the ClearMOT metric is also included.  If you have any questions, please contact jmzhang AT

If you download and use the tracker in research, we ask that you cite the above paper in the bibliography of your paper(s).

title={Online multi-person tracking by tracker hierarchy},
author={Zhang, Jianming and Presti, Liliana Lo and Sclaroff, Stan},
booktitle={Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on},

Code Changelog:

07.15.2013: Corrected a mistake in supplementary files -- the previous ground truth files for PETS sequences were wrong. Evaluation code was also added.

08.05.2012: Initial release.