@inproceedings{08b4e0e43a84495e84984c7a86ff93fb,
title = "Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving",
abstract = "A robust perception system is critical in autonomous driving. It is responsible for object detection, classification, and ranging under challenging circumstances. Camera and lidar sensors provide complementary information, and by combining these two modalities, we can increase the robustness and accuracy of the overall perception system. This paper presents the implementation of sensor fusion based perception using camera images and lidar point clouds for object detection and ranging in a real-time driving environment. The experiment results obtained with our test vehicle demonstrate that the perception of vehicle surroundings can be more effectively achieved by means of camera-lidar sensor fusion compared with using a single type of sensor.",
keywords = "autonomous driving, camera, lidar, object detection, perception, ranging, sensor fusion",
author = "Danish Khan and Minjin Baek and Kim, \{Min Young\} and \{Seog Han\}, Dong",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 27th Asia-Pacific Conference on Communications, APCC 2022 ; Conference date: 19-10-2022 Through 21-10-2022",
year = "2022",
doi = "10.1109/APCC55198.2022.9943618",
language = "English",
series = "APCC 2022 - 27th Asia-Pacific Conference on Communications: Creating Innovative Communication Technologies for Post-Pandemic Era",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "342--343",
booktitle = "APCC 2022 - 27th Asia-Pacific Conference on Communications",
address = "United States",
}