Point Cloud Library (PCL)
1.3.1
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The pcl_keypoints library contains implementations of two point cloud keypoint detection algorithms. Keypoints (also referred to as interest points) are points in an image or point cloud that are stable, distinctive, and can be identified using a well-defined detection criteron. Typically, the number of interest points in a point cloud will be much smaller than the total number of points in the cloud, and when used in combination with local feature descriptors at each keypoint, the keypoints and descriptors can be used to form a compact—yet descriptive—representation of the original data.
Classes | |
class | pcl::Keypoint |
Keypoint represents the base class for key points. More... | |
class | pcl::NarfKeypoint |
NARF (Normal Aligned Radial Feature) keypoints. More... | |
class | pcl::SIFTKeypoint |
SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More... | |
class | pcl::UniformSampling |
UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More... | |
Functions | |
std::ostream & | pcl::operator<< (std::ostream &os, const NarfKeypoint::Parameters &p) |
std::ostream& pcl::operator<< | ( | std::ostream & | os, |
const NarfKeypoint::Parameters & | p | ||
) | [inline] |
Definition at line 182 of file narf_keypoint.h.