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无重叠视域视频传感器外部参数自校准算法综述

A Survey on Extrinsic Self-calibration Algorithms for Cameras without Overlapping Field of Views
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摘要 视频传感器外部参数自校准,即确定视频传感器的坐标和转角,是实现视频传感器网络应用的重要前提.不同于有重叠视域的视频传感器网络,无重叠视域的视频传感器网络中的视频传感器之间没有可以共享的、可以辅助求解它们的外部参数的信息,所以实现无重叠视域视频传感器外部参数自校准更加富有挑战性.本文回顾了国内外学者在无重叠视域视频传感器外部参数自校准方面的研究工作,着重对目前已有的算法进行了详细的分类和介绍,最后从多方面综合评述了各种算法的性能. Extrinsic self-calibration of cameras, i.e., to automatically determine the extrinsic parameters of the cameras （position and orientation）, is regarded as an important preparatory requirement. However, if the cameras do not share overlapping field of views （FoVs）, they lack the common information, which is normally obtained from the shared FoVs and used to design the self-calibration algorithms. Hence, it is more difficult and challenging to design the extrinsic self-cMibration algorithm in non-overlapping camera networks. In this paper, the existing extrinsic camera self-calibration algorithms for non-overlapping camera networks are reviewed, classified and summarized in detail.
作者 王强 刘燕 沈毅
机构地区 哈尔滨工业大学航天学院控制科学与工程系
出处 《自动化学报》 EI CSCD 北大核心 2012年第1期1-11,共11页 Acta Automatica Sinica
基金 国家自然科学基金(61174016 61171197) 中国高等院校博士点项目科研基金(20102302110033)资助~~
关键词 外部参数 自校准 视频传感器网络 无重叠视域 Extrinsic parameters, self-calibration, camera networks, non-overlapping filed of views
分类号 TP391.41 [自动化与计算机技术—计算机应用技术] TP212.9 [自动化与计算机技术—检测技术与自动化装置] TN929.5 [电子电信—通信与信息系统]
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