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Radar-Lidar Sensor Fusion Sheme Using Occluded Depth Generation for Pedestrian Detection

Title
Radar-Lidar Sensor Fusion Sheme Using Occluded Depth Generation for Pedestrian Detection
Authors
Kwon, Seong KyungSon, Sang HyukHyun, EuginLee, Jin-HeeLee, Jonghun
DGIST Authors
Son, Sang HyukHyun, EuginLee, Jonghun
Issue Date
2018-12-15
Citation
2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017, 1811-1812
Type
Conference
ISBN
9781538626528
Abstract
Despite the development of sensors and their sensor fusion technologies, pedestrian detection technology is a still challenging topic. The pedestrian detection using LIDAR-RADAR fusion method hasn¡t yet been reported. We propose the occluded depth generation based LIDAR-RADAR sensor fusion scheme. The proposed method consists of object detection, occluded depth generation and then pedestrian detection. Objects within the occluded depth are detected by RADAR and an occluded object is estimated to a pedestrian by means of RADAR human Doppler distribution. © 2017 IEEE.
URI
http://hdl.handle.net/20.500.11750/9555
DOI
10.1109/CSCI.2017.322
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Hyun, Eugin  
  • Research Interests Radar system, Radar signal processing, Automotive radar, Surveillance radar, Commercial radar, Defence radar,
Files:
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Collection:
Department of Information and Communication EngineeringRTCPS(Real-Time Cyber-Physical Systems) Lab2. Conference Papers
Convergence Research Center for Future Automotive Technology2. Conference Papers


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