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Generation of 3D Line Segment Based on Disparity Data

机译：基于差异数据的3D线段生成

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This paper presents a new 3D line segment extraction method by using disparity map generated in the process of stereo matching. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by area-based stereo. Since the reference of the disparity can significantly reduce the number of feature matching combinations, feature matching error can be drastically minimized. One requirement of the disparity to be referenced is that it should be reliable to be used in feature matching. To measure the reliability of the disparity, in this paper, we employ the self-consistency of the disparity. Our suggested technique is applied to the detection of 3D line segments by 2D line matching using our hybrid stereo matching, which can be efficiently utilized in the generation of the rooftop model from urban images. The suggested method is evaluated on Avenches data set of Ascona aerial images. Experimental results indicate that the extracted 3D line segments have an average error of 0.5m and can be efficiently used to the construction of 3D site models using a simple 3D line grouping.
机译：本文通过使用立体声匹配过程中生成的视差图提出了一种新的3D线段提取方法。我们的技术的核心是通过基于区域的立体声评估的视差的参考来执行特征匹配。由于视差的参考可以显着减少特征匹配组合的数量，因此可以大大最小化特征匹配误差。要引用的差异的一个要求是它应该可靠地用于特征匹配。为了衡量差异的可靠性，在本文中，我们采用了差异的自我一致性。我们的建议技术应用于使用我们的混合立体声匹配的2D线匹配检测3D线段，可以有效地利用城市图像的屋顶模型的产生。在ASCONA航空图像的AVENCHES数据集上评估了建议的方法。实验结果表明，提取的3D线段的平均误差为0.5米，可以使用简单的3D线分组有效地建造3D站点模型。

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