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首页> 外文期刊>International journal of multimedia data engineering & management >Multiple Points Localization With Defocused Images
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Multiple Points Localization With Defocused Images

机译:多点定位与离焦图像

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摘要

3D points reconstruction has attracted increasing attentions both in computer vision and robotic intelligence areas. However, the real depth measurement still relies on depth measurement instruments. Although many measurement methods for depth exist, they usually need additional instruments, which always increase the cost of the measurement system. To better localize the position of 3D points without use of other instruments, a direct method is proposed which acquires depth from defocus of current images in this paper. The method utilizes the property of camera lens system and mechanism of SFM to remove the ambiguity of structure scale and the relative error between these 3D points. In addition, a multiple image setting for improving the robustness of depth estimation is proposed that can further eliminate depth error from some kinds of nature noises. Experiments on the real scene are implemented, which shows that the proposed method outperforms the ordinary 3D points localization method.
机译:3D积分重建吸引了计算机视觉和机器人智能地区的增加的关注。但是,真正的深度测量仍然依赖于深度测量仪器。虽然存在许多用于深度的测量方法,但它们通常需要额外的仪器,始终增加测量系统的成本。为了更好地本地化3D点的位置而不使用其他仪器,提出了一种直接方法,该方法从本文中获取了从当前图像的散焦的深度。该方法利用相机镜头系统的性质和SFM机制,以消除结构规模的模糊和这些3D点之间的相对误差。另外,提出了一种用于提高深度估计稳健性的多个图像设置,其可以进一步消除某些类型的自然噪声的深度误差。实现了实场的实验,这表明所提出的方法优于普通的3D点定位方法。

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