Features Tutorials¶
How 3D Features work in PCL¶
This document presents a basic introduction to the 3D feature estimation methodologies in PCL.
TestCode : None
Estimating Surface Normals in a PointCloud¶
This tutorial discusses the theoretical and implementation details of the surface normal estimation module in PCL.
TestCode : None
Normal Estimation Using Integral Images¶
In this tutorial we will learn how to compute normals for an organized point cloud using integral images.
TestCode : examples/official/Features/NormalEstimationUsingIntegralImages.py
Point Feature Histograms (PFH) descriptors¶
This tutorial introduces a family of 3D feature descriptors called PFH (Point Feature Histograms) and discusses their implementation details from PCL?fs perspective.
TestCode : None
Fast Point Feature Histograms (FPFH) descriptors¶
This tutorial introduces the FPFH (Fast Point Feature Histograms) 3D descriptor and discusses their implementation details from PCL?fs perspective.
TestCode : None
Estimating VFH signatures for a set of points¶
This document describes the Viewpoint Feature Histogram (VFH) descriptor, a novel representation for point clusters for the problem of Cluster (e.g., Object) Recognition and 6DOF Pose Estimation.
TestCode : None
How to extract NARF features from a range image¶
In this tutorial, we will learn how to extract NARF features from a range image.
TestCode : None
Moment of inertia and eccentricity based descriptors¶
In this tutorial we will learn how to compute moment of inertia and eccentricity of the cloud. In addition to this we will learn how to extract AABB and OBB.
TestCode : examples/official/Features/moment_of_inertia.py