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

Grzegorz Cielniak; Tom Duckett; Achim J. Lilienthal

doi:10.1016/j.robot.2010.02.004

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

Grzegorz Cielniak, Tom Duckett, Achim J. Lilienthal

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

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.

Original language	English
Pages (from-to)	435-443
Number of pages	9
Journal	Robotics and Autonomous Systems
Volume	58
Issue number	5
DOIs	https://doi.org/10.1016/j.robot.2010.02.004
State	Published - 31 May 2010
Externally published	Yes

Keywords

AdaBoost
Bayesian estimation
Colour vision
Occlusion detection
Thermal vision

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10.1016/j.robot.2010.02.004

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title = "Data association and occlusion handling for vision-based people tracking by mobile robots",

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.",

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AU - Lilienthal, Achim J.

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AB - 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.

KW - AdaBoost

KW - Bayesian estimation

KW - Colour vision

KW - Occlusion detection

KW - Thermal vision

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EP - 443

JO - Robotics and Autonomous Systems

JF - Robotics and Autonomous Systems

IS - 5

ER -

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

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Keywords

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