CODEWITHSUNDEEP
c++point-cloud-librarypoint-cloudsfeature-detection
queuer
queuer

Reputation: 25

How to visualize the result of pcl::FPFHEstimation in point cloud using PCL?

I'm using pcl::FPFHEstimation class to detect feature point like this:

pcl::FPFHEstimationOMP<pcl::PointXYZ, pcl::Normal, pcl::FPFHSignature33> fest;
pcl::PointCloud<pcl::FPFHSignature33>::Ptr object_features(new pcl::PointCloud<pcl::FPFHSignature33>());
fest.setRadiusSearch(feature_radius);
fest.setInputCloud(source_cloud);
fest.setInputNormals(point_normal);
fest.compute(*object_features);

My question is how to visulize detected feature points in pointcloud? like detected feature points in red color and non-feature points in white color.

I have searched a lot for this, but I only find some ways to display histogram which is not what I want.

Upvotes: 1

Views: 1262

Answers (1)

apalomer
apalomer

Reputation: 1925

Fast point feature histogram is a point descriptor (which in pcl comes in the form of pcl::FPFHSignature33). This means that the algorithm computes a histogram for all points in the input point cloud. Once the descriptors of the points are computed, then you can classify, segment... the points. But the process of classifying or segmenting the points would be another algorithm.

In this paper I use FPFH to coarsely align point clouds. In there I use the FPFH descriptors to decide which point from cloud A corresponds to which point from cloud B (associate points). In this publication, what I do is I compute the curvature for all points before the FPFH, and then, I only compute the FPFH of the subset of points that which curvature is above a given threshold. This is how I extract key points. Then, I use the FPFH of these key points fo the rest of the things (in my case associate points from different point clouds).

The analogy that you propose in one of your comments: "So the feature descriptor computed by FPFH is more like a multi-dimentional eigenvector or something " would be a good one.

So, to answer your question: No, there is no other tool apart from histograms to visualize the FPFH data (or at least not an out-of-the-box pcl class that you can use).

Upvotes: 2

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