首页> 外文会议>2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) >Simultaneous self-calibration of a projector and a camera using structured light
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Simultaneous self-calibration of a projector and a camera using structured light

机译:使用结构化光同时对投影仪和照相机进行自校准

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摘要

We propose a method for geometric calibration of an active vision system, composed of a projector and a camera, using structured light projection. Unlike existing methods of self-calibration for projector-camera systems, our method estimates the intrinsic parameters of both the projector and the camera as well as extrinsic parameters except a global scale without any calibration apparatus such as a checker-pattern board. Our method is based on the decomposition of a radial fundamental matrix into intrinsic and extrinsic parameters. Dense and accurate correspondences are obtained utilizing structured light patterns consisting of Gray code and phase-shifting sinusoidal code. To alleviate the sensitivity issue in estimating and decomposing the radial fundamental matrix, we propose an optimization approach that guarantees the possible solution using a prior for the principal points. We demonstrate the stability of our method using several examples and evaluate the system quantitatively and qualitatively.
机译:我们提出了一种使用结构化光投影对由投影仪和照相机组成的主动视觉系统进行几何校准的方法。与现有的用于投影仪-相机系统的自校准方法不同,我们的方法可以估算投影仪和相机的固有参数以及外部参数,但不使用诸如棋盘格样板之类的任何校准设备即可获得全局刻度。我们的方法基于将径向基本矩阵分解为内在和外在参数。利用由格雷码和相移正弦码组成的结构化光图案,可以获得密集而准确的对应关系。为了减轻估计和分解径向基矩阵时的敏感性问题,我们提出了一种优化方法,该方法可以确保使用先验的主要点来保证可能的解决方案。我们使用几个示例来证明我们方法的稳定性,并对系统进行定量和定性评估。

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