US 11,537,808 B2 · Method and system for classification of an object in a point cloud data set

Abstract

A method for classifying an object in a point cloud includes computing first and second classification statistics for one or more points in the point cloud. Closest matches are determined between the first and second classification statistics and a respective one of a set of first and second classification statistics corresponding to a set of N classes of a respective first and second classifier, to estimate the object is in a respective first and second class. If the first class does not correspond to the second class, a closest fit is performed between the point cloud and model point clouds for only the first and second classes of a third classifier. The object is assigned to the first or second class, based on the closest fit within near real time of receiving the 3D point cloud. A device is operated based on the assigned object class.

Claims20

Dependent claims

A method, comprising:

retrieving, by one or more processors, a three dimensional (3D) point cloud representing an object, the 3D point cloud comprising a plurality of point cloud data points;
determining, by the one or more processors, at least one feature variable based on at least one point cloud data point of the 3D point cloud;
determining, by the one or more processors, a first classification statistic based on the at least one feature variable;
determining, by the one or more processors, a second classification statistic based on the at least one feature variable;
assigning, by the one or more processors to the object, a selected object class from a plurality of object classes by determining a closest match between the object and the selected object class using the first classification statistic and the second classification statistic;
and
generating, by the one or more processors, a control signal to control operation of an autonomous vehicle based on the selected object class.

4 more elements

A light detection and ranging (LIDAR) system, comprising:

a sensor configured to:
generate a transmitted signal using a laser source;
output the transmitted signal;
receive a return signal responsive to the transmitted signal;
and
output a data signal representing at least one point cloud data point representing an object corresponding to the return signal;
and
a processing circuit configured to:
determine at least one feature variable based on the at least one point cloud data point;
determine a first classification statistic based on the at least one feature variable;
determine a second classification statistic based on the at least one feature variable;
assign a selected object class from a plurality of object classes to the object by determining a closest match between the object and the selected object class using the first classification statistic and the second classification statistic;
and
generate a control signal to control operation of an autonomous vehicle based on the selected object class.

11 more elements

Dependencies are inferred from the claim text.

Method and system for classification of an object in a point cloud data set

Life of this patent

Method and system for classification of an object in a point cloud data set

Life of this patent

Abstract

Claims20