Mathematical aspects of distortion calibration for digital cameras

IF 0.1 Q4 INSTRUMENTS & INSTRUMENTATION
Viacheslav S. Stadnichuk, V. Kolobrodov
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引用次数: 0

Abstract

Nowadays, most human processes are automated by means of computerization. This process has not spared the automotive industry. The latest developments in this field give promise that in the near future, cars will be completely autonomous. However, before that, there is an urgent need to address a number of issues, such as increasing the angle of view for greater coverage of the road with minimal space curvature. It is known that when the angle of view increases, so does the distortion (a mismatch in geometric similarity between an object and its image). This mismatch significantly reduces the accuracy of recognition algorithms. To solve this problem, this paper proposes a calibration method for cameras. The paper deals with mathematical aspects of distortion and the method of calibration of automobile chambers, and calibration errors. The method of static calibration without the use of points at infinity using static templates is proposed. A conventional camera has a small field of view (about 80 degrees). Such angle of view does not provide full scanning of the space; as a result, some of the necessary information remains outside the field of view, which is crucial for automotive industry because road signs, pedestrians, traffic lights might be missed. Therefore, in case of car cameras, the angle of view is increased by introducing distortion aberration. In this case, the field of view increases, yet the geometric similarity between the object and its image is affected. This, in turn, can affect the accuracy of computer vision algorithms. In order to keep the field of view angle large and the similarity between the subject and the object, it is necessary to calibrate the camera. In this paper, a calibration method for wide-angle car cameras is proposed and considered.
数码相机畸变校正的数学方面
如今,大多数人工过程都是通过计算机实现自动化的。这一过程并没有放过汽车行业。该领域的最新发展预示着在不久的将来,汽车将完全自动驾驶。然而,在此之前,迫切需要解决一些问题,例如增加视角,以最小的空间曲率扩大道路覆盖范围。众所周知,当视角增加时,失真也会增加(物体与其图像之间的几何相似性不匹配)。这种不匹配显著降低了识别算法的准确性。为了解决这个问题,本文提出了一种摄像机的标定方法。本文论述了畸变的数学方面、汽车气室的标定方法以及标定误差。提出了一种使用静态模板在不使用无穷远点的情况下进行静态校准的方法。传统的相机具有较小的视场(大约80度)。这样的视角不能提供对空间的完全扫描;因此,一些必要的信息仍然在视野之外,这对汽车行业至关重要,因为路标、行人和红绿灯可能会被遗漏。因此,在汽车摄像头的情况下,通过引入畸变像差来增加视角。在这种情况下,视野会增加,但对象与其图像之间的几何相似性会受到影响。这反过来又会影响计算机视觉算法的准确性。为了保持大的视场角和被摄体之间的相似性,有必要校准相机。本文提出并考虑了一种汽车广角摄像头的标定方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ukrainian Metrological Journal
Ukrainian Metrological Journal INSTRUMENTS & INSTRUMENTATION-
自引率
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发文量
21
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