MmWave Radar and Vision Fusion based Object Detection for Autonomous Driving: A Survey
2021
With autonomous driving developing in a booming stage, accurate object
detection in complex scenarios attract wide attention to ensure the safety of
autonomous driving. Millimeter wave (mmWave) radar and vision fusion is a
mainstream solution for accurate obstacle detection. This article presents a
detailed survey on mmWave radar and vision fusion based obstacle detection
methods. Firstly, we introduce the tasks, evaluation criteria and datasets of
object detection for autonomous driving. Then, the process of mmWave radar and
vision fusion is divided into three parts: sensor deployment, sensor
calibration and sensor fusion, which are reviewed comprehensively. Especially,
we classify the fusion methods into data level, decision level and feature
level fusion methods. Besides, we introduce the fusion of lidar and vision in
autonomous driving in the aspects of obstacle detection, object classification
and road segmentation, which is promising in the future. Finally, we summarize
this article.
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