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Dealing with the structured scene in visual odometry(VO): Incomplete SURF

机译:在视觉径管(VO)中处理结构化场景:不完整的冲浪

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In this paper we study the Visual Odometry (VO) in the structured environment. Harris, SURF, ORB, such feature extraction methods are often employed by current VO methods. They are good at corner detection, but, tend to fail in an environment full of structure lines. Here we focus on just one direction of the gradient, and modify the SURF method to make it fit in the specified scene, namely, the Incomplete SURF method. As it is supposed to run in a VO framework, the calculation of the transition matrix between frames has to be adjusted accordingly. We tried the proposed combined SURF and Incomplete SURF method in our self-established dataset (seldom corners, a lot of structure lines), and succeeded in estimating the transition matrix where pure SURF failed.
机译:在本文中,我们研究了结构化环境中的视觉内径(VO)。哈里斯,冲浪,ORB,这种特征提取方法通常通过电流VO方法采用。它们擅长角落检测,但是,在充满结构线的环境中倾向于失败。在这里,我们专注于梯度的一个方向,并修改冲浪方法使其适合在指定的场景中,即不完整的冲浪方法。由于它应该在VO框架中运行,必须相应地调整帧之间的转换矩阵的计算。我们尝试在我们自建立的数据集中提出的综合冲浪和不完整的冲浪方法(很少的角落,大量结构线),并成功估计纯冲浪失败的过渡矩阵。

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