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Object Depth Measurement from Monocular Images Based on Feature Segments

机译:基于特征分割的单眼图像目标深度测量

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Depth measurement technology plays an important role in the field of machine vision, and the depth measurement methods based on monocular vision have received more and more attention. However, previous depth measurement schemes based on single feature points and least squares calculation are susceptible to feature matching errors. To this end, this paper proposes a new object depth measurement method from monocular images based on feature segments. We use two images taken by the same camera and the pose information provided by GPS/IMU device to perform object depth measurement. The experiment based on the visual simulation software shows that the proposed method can improve the accuracy of the measurement results with a good robustness.
机译:深度测量技术在机器视觉领域中起着重要的作用,基于单眼视觉的深度测量方法越来越受到人们的关注。然而,先前基于单个特征点和最小二乘法计算的深度测量方案容易受到特征匹配误差的影响。为此,本文提出了一种新的基于特征片段的单眼图像深度测量方法。我们使用同一台摄像机拍摄的两个图像以及GPS / IMU设备提供的姿势信息来执行物体深度测量。基于视觉仿真软件的实验表明,该方法可以提高测量结果的准确性,并且具有良好的鲁棒性。

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