Influence of camera properties on image analysis in visual tunnel surveillance

R. Pflugfelder, H. Bischof, G. F. Domínguez, M. Nolle, H. Schwabach
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引用次数: 13

Abstract

CCTV and image analysis systems for automatic incident detection are major tools in tunnel safety management. This paper presents results of a feasibility study called VITUS-1. Among others, one aim of VITUS-I was to compare image analysis methods for robust object detection, tracking and incident detection. Image quality improvements were shown by using digital camera technology instead of state-of-the-art analogue CCTV. To improve image quality and robustness of existing image analysis methods, requirements on several camera properties were defined. We want to sensitise primarily tunnel operators and tunnel CCTV experts that commercial image analysis systems usually do not claim such requirements, e.g. requirements on resolution. This paper shows with a simple camera model that a robust detection of test objects is hardly feasible with typical tunnel CCTV (PAL resolution, 20/spl deg/ viewing angle, 212m camera distance). As a consequence, the specifications of tunnel CCTV should be adjusted to the needs of image analysis systems. Simple experiments with real video data show the applicability of the camera model.
隧道视觉监控中摄像机性能对图像分析的影响
用于事故自动检测的闭路电视和图像分析系统是隧道安全管理的主要工具。本文介绍了一项名为VITUS-1的可行性研究结果。其中,VITUS-I的一个目的是比较鲁棒目标检测、跟踪和事件检测的图像分析方法。通过使用数码相机技术而不是最先进的模拟CCTV,图像质量得到了改善。为了提高现有图像分析方法的图像质量和鲁棒性,定义了对相机若干属性的要求。我们希望让隧道营办商和隧道闭路电视专家认识到,商业图像分析系统通常不会提出这样的要求,例如分辨率要求。本文通过一个简单的摄像机模型表明,对于典型的隧道闭路电视(PAL分辨率,20/spl度/视角,212m摄像机距离),很难实现对测试对象的鲁棒检测。因此,隧道闭路电视的规格应根据图像分析系统的需要进行调整。实际视频数据的简单实验表明了摄像机模型的适用性。
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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