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Vehicles overtaking detection using RGB-D data

机译:使用RGB-D数据进行车辆超车检测

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摘要

Outstanding breakthrough in traffic video surveillance has been made with the development of computer vision techniques. However, there are still some problems to be solved due to the limitations of two-dimensional (2D) video data. With the popularity of three-dimensional (3D) cameras, high-quality color and depth data can be obtained simultaneously in real time through the video stream. In this paper, we propose a vehicles overtaking detection method using RGB-D data captured by the Kinect device in simulated traffic scenes. Vehicles are detected and tracked with a robust traffic scene understanding on RGB-D data. The depth data is utilized to recognize vehicles overtaking by analyzing the posture change of vehicles in different scenes. The principle of vehicles overtaking detection is to fit the line of vehicle side in the coordinate system and calculate the angle between the vehicle side and the road orientation. As a consequence, the posture change of the vehicle can be recognized. The proposed method is evaluated using simulation experiments which show that our work has good performance in vehicles overtaking detection and tracking.
机译:随着计算机视觉技术的发展,交通视频监控取得了突破性进展。但是,由于二维(2D)视频数据的局限性,仍然有一些问题需要解决。随着三维(3D)摄像机的普及,可以通过视频流同时实时获取高质量的颜色和深度数据。在本文中,我们提出了一种使用Kinect设备在模拟交通场景中捕获的RGB-D数据的车辆超车检测方法。借助对RGB-D数据的强大交通场景了解,可以检测和跟踪车辆。通过分析不同场景中车辆的姿态变化,深度数据用于识别车辆超车。车辆超车检测的原理是将车辆侧面的线拟合到坐标系中,并计算车辆侧面与道路方向之间的角度。结果,可以识别出车辆的姿势变化。仿真实验对提出的方法进行了评估,结果表明我们的工作在车辆超车检测和跟踪方面具有良好的性能。

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