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Optimal Exposure Estimation in the image for Structured Light System

机译:结构光系统图像的最佳曝光估计

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摘要

In this paper we propose a method of optimal camera exposure estimation in the image for a structured light system. In structured light system, it is important to discriminate the patterns form the captured images which are illuminated by the projector. But every object in real environments has a different reflection due to object's material and surface's color property, so the precise discrimination of the projected pattern from the image in indoor environments is a hard problem where many objects are located together especially. And the camera exposure setting is not good. For better 3D range data, we estimate the optimal exposure at pixels so that makes the illuminated light by the projector can be captured properly by the camera. In order to obtain the optimal exposures about specific environments in structured light system, we should know how much intensity and/or brightness varies while the exposure is changed. So we introduce the novel method to estimate intensity by characteristic curves. This proposed method overcomes the conventional method's exposure problem and presents what is the optimal exposure at pixels is and how to obtain this setting. This has been proved to be feasible in many applications which need to measure the objects with different surface properties.
机译:在本文中,我们提出了一种针对结构化光系统的图像中最佳相机曝光估计的方法。在结构光系统中,重要的是要区分由投影仪照亮的捕获图像中的图案。但是,由于物体的材料和表面的颜色特性,真实环境中的每个物体都有不同的反射,因此,在室内环境中,尤其是将许多物体放置在一起的情况下,要从图像中精确区分投影图案是一个难题。而且相机的曝光设置不好。为了获得更好的3D范围数据,我们估算了最佳像素曝光量,从而使投影机的照明光可以被相机正确捕获。为了获得有关结构化照明系统中特定环境的最佳曝光,我们应该知道在改变曝光时强度和/或亮度会发生多少变化。因此,我们介绍了一种通过特征曲线估计强度的新方法。提出的方法克服了传统方法的曝光问题,并提出了什么是像素的最佳曝光以及如何获得此设置。在许多需要测量具有不同表面特性的物体的应用中,这已被证明是可行的。

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