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An RGBD data based vehicle detection algorithm for vehicle following systems

机译:用于车辆跟踪系统的基于RGBD数据的车辆检测算法

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Autonomous vehicle following system is an important research issue in the ITS(Intelligent Transportation System). After reviewing some currently used environment perception sensors, this paper employs Kinect sensor as the main device in detecting the angle and distance of the leader vehicle in relation to the following vehicle. This paper also propose a vision-based algorithm to process RGB-D data. For the color image, we use template matching and Camshift algorithm to detect and track our desired target, the result of which is to get an approximately location of the target in the image and a search window of a certain scale, both of which are used in the disposition of the depth image. We use K-means clustering to distinguish the leader vehicle and the background so that we can determine the pose information of our target. Offline simulations and online experiments have been performed to evaluate the effectiveness of the algorithm. Both of them have shown the feasibility in the vehicle following system.
机译:自主车辆跟踪系统是ITS(Intelligent Transportation System,智能交通系统)中一个重要的研究课题。在回顾了一些当前使用的环境感知传感器之后,本文采用Kinect传感器作为主要设备,以检测引导车辆相对于跟随车辆的角度和距离。本文还提出了一种基于视觉的算法来处理RGB-D数据。对于彩色图像,我们使用模板匹配和Camshift算法来检测和跟踪所需目标,其结果是获得目标在图像中的大致位置以及一定比例的搜索窗口,这两种方法都可以使用在深度图像的配置中。我们使用K均值聚类来区分领导者车辆和背景,以便我们可以确定目标的姿态信息。已经进行了离线仿真和在线实验以评估算法的有效性。他们两个都显示了在车辆跟踪系统中的可行性。

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