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Research on features matching method for visual odometry based on depth image

机译:基于深度图像的视觉径测量特性匹配方法研究

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The unmanned aerial vehicle needs an effective visual odometry system intask of indoor. The sparse visual odometry of RGB-D sensor is difficult to extractor enough color image features in darkness environment of indoor, which results in the failure of matching. We present a method that extract 2D features from the depth image directly. The paper discussed the matching performance of ORB, FREAK and SURF descriptor to the depth image. The results of the experiments show that it is feasible extractor 2D features from the depth image to matching in visual odometry, the ORB descriptor is better than other methods suitable for this kind of application.
机译:无人驾驶飞行器需要一个有效的室内视觉测量系统intask。 RGB-D传感器的稀疏视觉测量仪难以提取足够的室内黑暗环境中的彩色图像特征,从而导致匹配的失败。我们提出了一种方法,即直接从深度图像中提取2D特征。本文讨论了对深度图像的ORB,Freak和Surf描述符的匹配性能。实验结果表明,它是从深度图像到视觉测量中的匹配的可行提取器2D特征,ORB描述符优于适用于这种应用的其他方法。

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