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首页> 外文期刊>Vehicular Technology, IEEE Transactions on >Feature Extraction in Scanning Laser Range Data Using Invariant Parameters: Application to Vehicle Detection
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Feature Extraction in Scanning Laser Range Data Using Invariant Parameters: Application to Vehicle Detection

机译:不变参数扫描激光测距数据中的特征提取:在车辆检测中的应用

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摘要

This paper presents a feature extraction method in scanning laser range data. Many authors have studied this problem by proposing solutions that rely on a modeling of the scene in Cartesian coordinates. These methods are based on the computation of the interscan distance between two consecutive measurements, which, in practice, is not very easy to estimate. Our proposed method, i.e., segmentation using invariant parameters (SIP), deals with laser measurements in natural coordinates, which avoids any preprocessing stage that could modify the measurement noise statistics. This approach is founded on the use of an invariant description of the feature and leads to the definition of a criterion of line-segment detection that only depends on the sensor intrinsic parameters.
机译:本文提出了一种扫描激光测距数据的特征提取方法。许多作者通过提出依赖于笛卡尔坐标系中的场景建模的解决方案来研究此问题。这些方法基于两次连续测量之间的扫描间距离的计算,实际上这并不是很容易估计的。我们提出的方法,即使用不变参数(SIP)进行分割,以自然坐标处理激光测量,从而避免了任何可能修改测量噪声统计数据的预处理阶段。该方法基于对特征的不变描述的使用,并导致仅取决于传感器固有参数的线段检测标准的定义。

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