智能摄像机网络:无歧义自动校准的分析框架

K. Vupparaboina, Kamala Raghavan, S. Jana
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引用次数: 5

摘要

随着智能环境的普及,智能多摄像头网络的重要性日益凸显。具体来说,这种摄像机网络的非侵入式校准在远程呈现系统等智能应用中变得必不可少,其中需要在不断变化的内部和外部摄像机参数的动态设置中执行多视图成像/记录。不幸的是,众所周知,流行的自动校准方法会引入歧义或需要人工干预。在此背景下,我们提出了一种具有已知基线距离的立体对和任意位置的附加(单声道)摄像机的三摄像机配置(可以推广),并在该配置中解析地建立了自动校准的唯一性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart camera networks: An analytical framework for auto calibration without ambiguity
With the proliferation of smart environment, smart multi-camera networks assume growing significance. Specifically, non-intrusive calibration of such camera networks becomes imperative in smart applications such as telepresence systems, where multi-view imaging/recording needs to be performed in a dynamic setting with continuously changing intrinsic and extrinsic camera parameters. Unfortunately, popular auto calibration methods are known to introduce ambiguity or require manual intervention. In this backdrop, we propose a three-camera configuration (which can be generalized) with a stereo pair having known baseline distance and an additional (mono) camera positioned arbitrarily, and analytically establish the uniqueness of auto calibration in the proposed configuration.
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