Data association and occlusion handling for vision-based people tracking by mobile robots

Authors:
Grzegorz Cielniak;Tom Duckett;Achim J. Lilienthal
Affiliations:
School of Computer Science, University of Lincoln, LN6 7TS Lincoln, United Kingdom;School of Computer Science, University of Lincoln, LN6 7TS Lincoln, United Kingdom;Centre for Applied Autonomous Sensor Systems, Örebro University, SE-701 82 Örebro, Sweden
Venue:
Robotics and Autonomous Systems
Year:
2010

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Abstract

This paper presents an approach for tracking multiple persons on a mobile robot with a combination of colour and thermal vision sensors, using several new techniques. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is incorporated into the tracker. The paper presents a comprehensive, quantitative evaluation of the whole system and its different components using several real world data sets.