@inproceedings{e9fc45a2f0cd4c5ab83fc14d986ea2c6,
title = "Radar and Vision Sensor Fusion for Object Detection in Autonomous Vehicle Surroundings",
abstract = "Multi-sensor data fusion for advanced driver assistance systems (ADAS) in the automotive industry has received much attention recently due to the emergence of self-driving vehicles and road traffic safety applications. Accurate surroundings recognition through sensors is critical to achieving efficient advanced driver assistance systems (ADAS). In this paper, we use radar and vision sensors for accurate object recognition. However, since sensor-specific data have different coordinates, the data coordinate calibrate is essential. In this paper, we introduce the coordinate calibration algorithms between radar and vision images and perform sensor calibrating using data obtained from actual sensors.",
keywords = "Autonomous Vehicle, radar, Sensor calibration, Sensor fusion, Vision",
author = "Jihun Kim and Han, {Dong Seog} and Benaoumeur Senouci",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 ; Conference date: 03-07-2018 Through 06-07-2018",
year = "2018",
month = aug,
day = "14",
doi = "10.1109/ICUFN.2018.8436959",
language = "English",
isbn = "9781538646465",
series = "International Conference on Ubiquitous and Future Networks, ICUFN",
publisher = "IEEE Computer Society",
pages = "76--78",
booktitle = "ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks",
address = "United States",
}