Non-linear, shape independent object tracking based on 2D lidar data

The paper presents a new lidar-based approach to object tracking. To this end, range data are recorded by two vehicle-born lidar scanners and registered in a common coordinate system. In contrary to common approaches, particle filters are employed to track the objects. This ensures no linearization...

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Bibliographic Details
Published in2009 IEEE Intelligent Vehicles Symposium pp. 532 - 537
Main Authors Thuy, Michael, Puente Leon, Fernando
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
Subjects
Cameras
Estimation error
Face detection
Laser radar
Object detection
Particle filters
Particle tracking
Radar tracking
Robustness
Shape
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Summary:The paper presents a new lidar-based approach to object tracking. To this end, range data are recorded by two vehicle-born lidar scanners and registered in a common coordinate system. In contrary to common approaches, particle filters are employed to track the objects. This ensures no linearization of the underlying non-linear process model and, thus, a decreasing estimation error. For the object association, a new method is proposed that considers the knowledge about the object shape as well. Based on a statistical formulation, this ensures a robust object assignment even in ambiguous traffic scenes.
ISBN:9781424435036
142443503X
ISSN:1931-0587
2642-7214
DOI:10.1109/IVS.2009.5164334