Liu Shengxiong, Yang Xiuju, Cui Jianguo, Yin Zhiyong
Department of Biomedical Engineering, School of Pharmacy & Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
Chongqing Bayi Forensic Science Identification Center for Road Traffic Accidents, Chongqing, 400042, China.
J Forensic Sci. 2017 Jul;62(4):1071-1074. doi: 10.1111/1556-4029.13381. Epub 2017 Jan 9.
In traffic forensic identifications, it was usually unfavorable that estimated velocities of questioned vehicles derived from frame-based methods eventually turned out to be close to but a bit less than speed limits. In this paper, a novel pixel-based method was presented to estimate vehicles' relatively instantaneous velocities. First, two adjacent pixels' actual distance was acquired from the closed-circuit television (CCTV) images. Then, the instantaneous average velocity within this one frame interval time (FIT) was calculated out. The frame-based method and its evaluating result were also introduced in this paper. The results showed that the velocity estimated by this new pixel-based method was higher than which derived from the frame-based method. Employing this presented novel method in these cases, it could be more accurately identified whether or not the vehicles had exceeded the speed limits, and then the responsibilities could be consequently assigned impartially.
在交通法医鉴定中,基于帧的方法得出的涉案车辆估计速度最终接近但略低于速度限制,这种情况通常是不利的。本文提出了一种基于像素的新颖方法来估计车辆的相对瞬时速度。首先,从闭路电视(CCTV)图像中获取两个相邻像素的实际距离。然后,计算出该一帧间隔时间(FIT)内的瞬时平均速度。本文还介绍了基于帧的方法及其评估结果。结果表明,这种基于像素的新方法估计的速度高于基于帧的方法得出的速度。在这些情况下采用这种提出的新方法,可以更准确地确定车辆是否超速,进而公正地划分责任。