利用图像模糊分析确定运动车辆的动态特性

D. Loktev, A. Loktev, V. Korolev, Andrey A. Linenko
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引用次数: 0

摘要

研究了一种从图像上识别车辆并确定其动态特性的方法。控制及时确定的特征将允许检测车辆的违规行为,包括车辆重量过重,这会导致道路磨损和损坏增加。对于目标检测,使用卷积神经网络。Hough和Canny检测器用于确定物体边界和车轮轴。详细介绍了两轴二手车模型。在检测并确定车辆轮轴数后,采用被动图像分析方法选择车辆的垂直振动模型,并根据得到的几何和运动学参数确定车辆的动态特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining the Dynamic Characteristics of Moving Vehicles Using Image Blur Analysis
A method to recognize vehicles on an image and to determine their dynamic characteristics is considered. Control of timely determined characteristics will allow detecting violations of vehicles, including excessive vehicle weight, which leads to increased wear and damage to the roadway. For object detection the convolutional neural network is used. Hough and Canny detectors are used to determine object boundaries and wheel axles. The used vehicle model with two axles in detail is described. After detecting and determining the number of wheel axles of the vehicle, a model of vertical oscillations of the vehicle is selected by the passive method of image analysis, and based on the obtained geometric and kinematic parameters, the dynamic characteristics of the vehicle are determined.
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