基于单目视觉的非水平目标测量方法

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS
Jiajin Lang, Jiafa Mao, Ronghua Liang
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引用次数: 2

摘要

随着计算机视觉技术的发展,目标测量方法在机器人自动避障、车辆辅助驾驶等系统中得到了广泛的应用。目标测量技术有很多,但大多数是基于双目或三眼视觉,或基于单眼视觉加上其他辅助设备,或基于单眼视觉测量水平目标。前两种技术通过增加数据量和牺牲处理速度来实现精确定位,而第三种技术只研究水平目标的测量方法。针对多设备测量方法的复杂性和水平目标单目视觉测量方法的局限性,提出了一种新的非水平目标单目视觉测量方法。根据相机成像原理、相机内外参数和模数转换原理,推导了测量非水平目标相对高度和目标距离的成像关系模型,并用数学方法证明了该模型的可解性。实验结果验证了该方法的正确性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-horizontal target measurement method based on monocular vision
With the development of computer vision technology, target measurement methods have been widely used in robot automatic obstacle avoidance, vehicle-assisted driving and other systems. There are many target measurement technologies available, but most of them are based on binocular or trinocular vision, or based on monocular vision with other auxiliary equipment, or based on monocular vision to measure horizontal target. The first two technologies achieve precise positioning by increasing the amount of data and sacrificing processing speed, while the third only studies the measurement method of the horizontal target. To address the complexity of the multi-equipment measurement methods and the limitation of the monocular measurement methods for horizontal target, this paper proposes a novel monocular vision measurement method for the non-horizontal target. According to the principle of camera imaging, internal and external parameters of the camera and analogue-to-digital conversion principle, the imaging relationship model for measuring the relative height and target distance of non-horizontal target is deduced, and the solvability of the model is demonstrated by mathematics. The experimental results verify the correctness and feasibility of this method.
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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