The paper addresses the problem of object perception for intelligent vehicle applications with main tasks of detection, tracking and classification of obstacles where multiple sensors (i.e.: lidar, camera and radar) are used. New algorithms for raw sensor data processing and sensor data fusion are introduced making the most information from all sensors in order to provide a more reliable and accurate information about objects in the vehicle environment. The proposed object perception module is implemented and tested on a demonstrator car in real-life traffics and evaluation results are presented.
Object perception for intelligent vehicle applications: A multi-sensor fusion approach
01.06.2014
2320868 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
OBJECT PERCEPTION FOR INTELLIGENT VEHICLE APPLICATIONS: A MULTI-SENSOR FUSION APPROACH
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