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首页> 外文期刊>SAE International Journal of Advances and Current Practices in Mobility >Stationary and Moving Camera Video Analysis Compared to Known Reference System
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Stationary and Moving Camera Video Analysis Compared to Known Reference System

机译：与已知参考系统相比，固定和移动的相机视频分析

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摘要

Video recordings of vehicular collisions have become widely available to the accident reconstructionist and can play a vital role in determining the locations and speeds of the subject vehicles involved in a collision. However, due to varying video resolutions, framerate, lens distortion, motion blur, and camera movement, errors in video analysis can occur. To understand the total error inherent to video analysis, this study presents analysis of videos from different video systems, the limitations in the analysis, and a comparison of video analysis speeds to reference datasets. The factors that influenced variance included resolution, lens correction, shutter speed, and framerate. The video systems analyzed included three moving cameras and two stationary units. In the present study, a mock collision scenario in which a target vehicle approached a recording vehicle head-on, was staged to emulate an actual event captured on video. The target vehicle's speed was analyzed using the captured videos. The video analysis results were then compared to the speeds obtained from the target vehicle's wheel speed sensors via a VBOX system connected to the vehicle's Controlled Area Network (CAN), and VBOX GPS position data. The videos were recorded from two locations. Location 1 was at the top corner of a business complex. This location was equipped with two video cameras: a GoPro HERO5 and a Sony α6400 mirrorless camera. Location 2 was within the recording vehicle itself. This location was equipped with three video systems: a 2018 Tesla Model 3 Dashcam video camera system, a generic dashboard video system with a low framerate, and a Blackmagic Design camera. Videos were captured as the recording vehicle moved towards the target vehicle; the camera's location and angle relative to the target were constantly changing. Errors in the determined speeds were quantified based on comparison of the video analysis speeds to the reference datasets. The errors in speed were determined to be inversely correlated to the video resolution. Additionally, the analysis of the video footage from the stationary source yielded lower error than the analysis of the moving vehicle video for a given resolution and framerate.
机译：车辆碰撞的视频录制已广泛可用于事故重建主义者，并且可以在确定碰撞中涉及的主题车辆的位置和速度方面发挥至关重要的作用。但是，由于视频分辨率有所不同，帧速率，镜头失真，运动模糊和摄像头运动可能会发生视频分析中的错误。为了了解视频分析固有的总误差，本研究介绍了来自不同视频系统的视频，分析中的局限性以及视频分析速度与参考数据集的比较。影响方差的因素包括分辨率，镜头校正，快门速度和帧速率。分析的视频系统包括三个移动摄像机和两个固定单元。在本研究中，针对目标车辆直接接近录音车辆的模拟碰撞场景，以模拟视频中捕获的实际事件。使用捕获的视频分析了目标车辆的速度。然后，将视频分析结果与通过连接到车辆受控区域网络（CAN）和Vbox GPS位置数据的Vbox系统从目标车辆车轮速度传感器获得的速度进行比较。这些视频是从两个位置录制的。位置1位于商业综合体的顶角。该位置配备了两个摄像机：GoPro Hero5和Sonyα6400无反光镜相机。位置2在录音车辆本身内。该位置配备了三个视频系统：2018 Tesla Model 3 Dashcam摄像机系统，一个带有低帧率的通用仪表板视频系统和闪光设计摄像头。当录音车辆向目标车辆移动时，视频被捕获。相机相对于目标的位置和角度正在不断变化。根据视频分析速度与参考数据集的比较，确定速度中的错误是量化的。速度错误被确定为与视频分辨率成反比。此外，对固定源的视频录像的分析产生的误差低于对给定分辨率和帧率的移动车辆视频的分析。

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