汽车工业
目标检测
计算机视觉
对象(语法)
人工智能
计算机科学
闭塞
行人检测
感知
行人
视觉对象识别的认知神经科学
人机交互
工程类
模式识别(心理学)
运输工程
心理学
医学
航空航天工程
神经科学
心脏病学
作者
Shane Gilroy,Edward Jones,Martin Glavin
标识
DOI:10.1109/tits.2019.2956813
摘要
Accurate and consistent vulnerable road user detection remains one of the most challenging perception tasks for autonomous vehicles. One of the most complex outstanding issues is partial occlusion, where a sensor has only a partial view of the target object due to a foreground object that partially obscures the target. A review of occlusion detection and handling solutions for the automotive environment is presented by this research. This article first discusses object detection by the human visual system, provides an overview of occlusion reasoning in computer vision, presents a summary of occlusion handling strategies in pedestrian, vehicle and object detection applications in the automotive environment. A selection of the remaining challenges to achieving the required level of object detection performance for safe autonomous driving are also discussed.
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