首页> 外国专利> SYSTEM AND METHOD FOR ORDERED REPRESENTATION AND FEATURE EXTRACTION FOR POINT CLOUDS OBTAINED BY DETECTION AND RANGING SENSOR

SYSTEM AND METHOD FOR ORDERED REPRESENTATION AND FEATURE EXTRACTION FOR POINT CLOUDS OBTAINED BY DETECTION AND RANGING SENSOR

机译:检测和测距传感器获得的点云的有序表示和特征提取的系统和方法

摘要

A method is described which includes receiving a point cloud having a plurality of data points each representing a 3D location in a 3D space, the point cloud being obtained using a detection and ranging (DAR) sensor. For each data point, associating the data point with a 3D volume containing the 3D location of the data point, the 3D volume being defined using a 3D lattice that partitions the 3D space based on spherical coordinates. For at least one 3D volume, the data points are sorted within the 3D volume based on at least one dimension of the 3D lattice; and the sorted data points are stored as a set of ordered data points. The method also includes performing feature extraction on the set of ordered data points to generate a set of ordered feature vectors and providing the set of ordered feature vectors to perform a machine learning inference task.
机译:描述了一种方法,该方法包括:接收具有多个数据点的点云,每个数据点代表3D空间中的3D位置,该点云是使用检测和测距(DAR)传感器获得的。对于每个数据点,将数据点与包含数据点3D位置的3D体积相关联,使用3D晶格定义3D体积,该3D晶格基于球坐标来划分3D空间。对于至少一个3D体积,基于3D晶格的至少一维在3D体积内对数据点进行排序。并将排序的数据点存储为一组有序数据点。该方法还包括对一组有序数据点执行特征提取以生成一组有序特征向量,并提供该组有序特征向量以执行机器学习推理任务。

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