基于分类标记多伯努利滤波的多摄像头红绿灯识别

Martin Bach, Stephan Reuter, K. Dietmayer
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引用次数: 9

摘要

对于自动驾驶汽车来说,正确处理复杂的红绿灯控制十字路口仍然是一个挑战。虽然许多基于图像的方法解决了近距离识别问题,但在远距离的早期红绿灯检测对于节能驾驶领域至关重要。为此,本文提出了一种由多个车载摄像头组成的交通灯检测系统,即使在200米以上的距离也能检测到交通灯。此外,所提出的系统是基于跟踪技术,使用标记多伯努利滤波器,结合基于Dempster-Shafer证据理论的分类融合。该系统在德国收集的真实世界数据集上进行了测试,并通过多摄像头方法证明了性能的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-camera traffic light recognition using a classifying Labeled Multi-Bernoulli filter
The correct handling of complex traffic-light-controlled intersections is still a challenge for automated vehicles. While a number of image-based approaches tackle close-range recognitions, an early traffic light detection at high distances is of great importance in the area of energy-efficient driving. For this reason, a traffic light detection system consisting of multiple on-board cameras is presented in this work, enabling the detection of traffic lights even from a distance of more than 200m. Furthermore, the presented system is based on tracking techniques using a Labeled Multi-Bernoulli filter in combination with the fusion of classifications based on the Dempster-Shafer theory of evidence. The system was tested on a real world data set collected in Germany and an increase in performance was demonstrated by a multi-camera approach.
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