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Inexpensive Ground Truth and Performance Evaluation for Human Tracking using multiple Laser Measurement Sensors

Published

Author(s)

William P. Shackleford, Tsai Hong Hong, Tommy Chang

Abstract

This paper will describe a flexible and inexpensive method of obtaining ground truth for the evaluation of Human Tracking systems. It is expected to be appropriate for evaluating systems used to allow robots and/or autonomous vehicles to operate safely around humans. It is currently focused on tracking people as they stand still or walk. It relies on multiple Laser Measurement Sensors(LMS) also called laser line scanners. The LMS's are mounted to scan in a horizontal plane. A method for quickly calibrating the relative position and orientation of each of the sensors to each other is described. A basic human tracking algorithm using the LMS's is described and how the algorithm can be combined with apriori knowledge of the walkers intended path during the test. A graphical user interface(GUI) displays both the data obtained directly from the LMS and the output of the tracking algorithm. The GUI allows the user to verify and adjust the tracking algorithm without needing to annotate every frame, and therefore at a lower cost than systems that require extensive annotation. Tests will be performed with people standing still and multiple scans taken at different heights to determine how the computed persons position varies with height selected to do the scan. Tests with people moving along a 40 m corridor at varying walking/running speeds will measure both the effects of speed and distance from the sensor.
Proceedings Title
Proceedings of the 2010 Performance Metrics for Intelligent Systems (PerMIS) Workshop
Conference Dates
September 28-30, 2010
Conference Location
Baltimore, MD

Keywords

Human Tracking, Laser Measurement Sensor(LMS), Ground Truth

Citation

Shackleford, W. , , T. and Chang, T. (2010), Inexpensive Ground Truth and Performance Evaluation for Human Tracking using multiple Laser Measurement Sensors, Proceedings of the 2010 Performance Metrics for Intelligent Systems (PerMIS) Workshop, Baltimore, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=906630 (Accessed June 15, 2024)

Issues

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Created October 27, 2010, Updated February 19, 2017