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Conference Papers Year : 2014

Object Perception for Intelligent Vehicle Applications: A Multi-Sensor Fusion Approach

Abstract

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.
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Dates and versions

hal-01019527 , version 1 (07-07-2014)

Identifiers

  • HAL Id : hal-01019527 , version 1

Cite

Trung-Dung Vu, Olivier Aycard, Fabio Tango. Object Perception for Intelligent Vehicle Applications: A Multi-Sensor Fusion Approach. Intelligent Vehicles Symposium, 2014 IEEE, Jun 2014, Dearborn, MI, United States. pp.100-106. ⟨hal-01019527⟩
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