基于非重叠区域的多摄像机目标跟踪技术分析-analysis of multi-camera target tracking technology based on non-overlapping region.docx
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基于非重叠区域的多摄像机目标跟踪技术分析-analysis of multi-camera target tracking technology based on non-overlapping region
摘 要近年来,随着视频监控技术的发展和人们对智能化监控要求的日益提高,传统的单摄 像机监控系统在很多场合已无法满足视频监控的要求。与之相比,使用多个摄像机协作可 以扩大摄像机的观测范围、增加观测角度、更全面地捕捉运动对象的信息、克服遮挡等问 题。因此,越来越受到人们的关注。其中,当多摄像机系统用于监控范围较大的场合时, 相邻摄像机的视域之间往往没有交叠区域,于是产生了基于无重叠视域的多摄像视频监 控,这一具有实用价值的研究方向。在无重叠视域的多摄像机监控环境中,同一目标在不同摄像机中,往往会因为光照的 差异、目标姿势的变化,以及摄像机自身因素的影响,而表现出不同的外观特征,影响了 目标跟踪匹配的准确性。本文针对上述问题,研究了基于无重叠视域的多摄像机目标跟踪 匹配技术。主要研究内容和创新点如下:(1) 研究了亮度转换函数的建立方法,提出了一种根据摄像机场景亮度进行亮度转换 函数调整的有效方法。在建立多摄像机监控场景间的亮度映射关系前,先进行场景亮度判 断,以确定映射方向,再根据目标的归一化累积直方图,建立亮度转换函数,在一定程度 上避免了部分亮度映射的缺失。并验证了进行亮度转换的必要性。(2) 分析了平均亮度转换函数和累积亮度转换函数的性质,在此基础上,综合了多帧 和多目标的思想,提出了一种综合的亮度转换函数。并引入了修正的 Bhattacharyya 系数, 用以衡量亮度映射关系的准确度。实验结果表明,改进的亮度转换函数映射关系更为准确。(3) 提出了一种基于多帧匹配的亮度转换函数概率主成分分析的目标匹配算法。通过 训练多对目标的关键帧形成亮度转换函数集,然后使用概率主成分分析对函数空间进行概 率估计,采用多帧匹配的方法,计算目标之间的亮度转换函数属于函数空间的概率。同时 考虑到训练目标不足,结合改进的亮度转换函数的方法,采用多帧匹配计算目标直方图之 间的相似度。实验结果表明该方法具有良好的匹配效果。文章的最后给出了对全文的总结,并结合现有的研究状况,展望该课题可进一步挖掘 的内容。关键词:多摄像机,无重叠视域,亮度转换函数,概率主成分分析,多帧匹配AbstractIn recent years, with the rapid development of technology in video surveillance, and the increasing demand for intelligent monitoring, the traditional single-camera monitoring system has failed to meet the requirement of video surveillance on many situations. Compared with single-camera monitoring system, using multiple cameras can expand observation range, increase observation angle, capture more information of moving objects, and deal with the problem of occlusions. Therefore, it has been attracted more and more attentions. It often does not have overlapping views between adjacent cameras on many occasions, especially when multi-camera system monitors a large range of occasions. Therefore, multi-camera video surveillance based on non-overlapping views becomes a direction for research with practical value.In the environment for multi-camera surveillance based on non-overlapping views, the appearance of an object in one camera view might be very different from its appearance in another camera view due to the differences in illumination, pose and camera properties, affecting the accura
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