Detailed Description

Collaboration diagram for Feature detection, descriptors and matching:

Classes
class	mrpt::vision::CFeature
	A generic 2D feature from an image, extracted with CFeatureExtraction Each feature may have one or more descriptors (see descriptors), in addition to an image patch. More...

class	mrpt::vision::CFeatureList
	A list of visual features, to be used as output by detectors, as input/output by trackers, etc. More...

class	mrpt::vision::CMatchedFeatureList
	A list of features. More...

class	mrpt::vision::CFeatureExtraction
	The central class from which images can be analyzed in search of different kinds of interest points and descriptors computed for them. More...

struct	mrpt::vision::TSimpleFeature_templ< PIXEL_COORD_TYPE >
	A simple structure for representing one image feature (without descriptor nor patch) - This is the template which allows you to select if pixels are represented as integers or floats. More...

struct	mrpt::vision::TSimpleFeatureTraits< FEATURE >

struct	mrpt::vision::TSimpleFeatureTraits< TSimpleFeature >

struct	mrpt::vision::TSimpleFeatureTraits< TSimpleFeaturef >

struct	mrpt::vision::TSimpleFeatureList_templ< FEATURE >
	A list of image features using the structure TSimpleFeature for each feature. More...

struct	mrpt::vision::KeypointResponseSorter< FEATURE_LIST >
	A helper struct to sort keypoints by their response: It can be used with these types: More...

class	mrpt::vision::CFeatureListKDTree< FEAT >
	Helper class: KD-tree search class for vector<KeyPoint>: Call mark_as_outdated() to force rebuilding the kd-tree after modifying the linked feature list. More...

Typedefs
using	mrpt::vision::TSimpleFeature = TSimpleFeature_templ< mrpt::img::TPixelCoord >
	A simple structure for representing one image feature (without descriptor nor patch). More...

using	mrpt::vision::TSimpleFeaturef = TSimpleFeature_templ< mrpt::img::TPixelCoordf >
	A version of TSimpleFeature with subpixel precision. More...

using	mrpt::vision::TSimpleFeatureList = TSimpleFeatureList_templ< TSimpleFeature >
	A list of image features using the structure TSimpleFeature for each feature. More...

using	mrpt::vision::TSimpleFeaturefList = TSimpleFeatureList_templ< TSimpleFeaturef >
	A list of image features using the structure TSimpleFeaturef for each feature - capable of KD-tree computations. More...

Functions
template<class DESCRIPTOR_KDTREE >
size_t	mrpt::vision::find_descriptor_pairings (std::vector< std::vector< size_t >> pairings_1_to_multi_2, std::vector< std::pair< size_t, size_t >> pairings_1_to_2, const CFeatureList &feats_img1, const DESCRIPTOR_KDTREE &feats_img2_kdtree, const mrpt::vision::TDescriptorType descriptor=descSIFT, const size_t max_neighbors=4, const double max_relative_distance=1.2, const typename DESCRIPTOR_KDTREE::kdtree_t::DistanceType max_distance=std::numeric_limits< typename DESCRIPTOR_KDTREE::kdtree_t::DistanceType >::max())
	Search for pairings between two sets of visual descriptors (for now, only SURF and SIFT features are considered). More...

Static methods with low-level detector functionality
static void	mrpt::vision::CFeatureExtraction::detectFeatures_SSE2_FASTER9 (const mrpt::img::CImage &img, TSimpleFeatureList &corners, const int threshold=20, bool append_to_list=false, uint8_t octave=0, std::vector< size_t > *out_feats_index_by_row=nullptr)
	A SSE2-optimized implementation of FASTER-9 (requires img to be grayscale). More...

static void	mrpt::vision::CFeatureExtraction::detectFeatures_SSE2_FASTER10 (const mrpt::img::CImage &img, TSimpleFeatureList &corners, const int threshold=20, bool append_to_list=false, uint8_t octave=0, std::vector< size_t > *out_feats_index_by_row=nullptr)
	Just like detectFeatures_SSE2_FASTER9() for another version of the detector. More...

static void	mrpt::vision::CFeatureExtraction::detectFeatures_SSE2_FASTER12 (const mrpt::img::CImage &img, TSimpleFeatureList &corners, const int threshold=20, bool append_to_list=false, uint8_t octave=0, std::vector< size_t > *out_feats_index_by_row=nullptr)
	Just like detectFeatures_SSE2_FASTER9() for another version of the detector. More...

Typedef Documentation

◆ TSimpleFeature

using mrpt::vision::TSimpleFeature = typedef TSimpleFeature_templ<mrpt::img::TPixelCoord>

A simple structure for representing one image feature (without descriptor nor patch).

See also: TSimpleFeaturef, CFeature, TSimpleFeatureList

Definition at line 82 of file TSimpleFeature.h.

◆ TSimpleFeaturef

using mrpt::vision::TSimpleFeaturef = typedef TSimpleFeature_templ<mrpt::img::TPixelCoordf>

A version of TSimpleFeature with subpixel precision.

Definition at line 85 of file TSimpleFeature.h.

◆ TSimpleFeaturefList

using mrpt::vision::TSimpleFeaturefList = typedef TSimpleFeatureList_templ<TSimpleFeaturef>

A list of image features using the structure TSimpleFeaturef for each feature - capable of KD-tree computations.

Definition at line 297 of file TSimpleFeature.h.

◆ TSimpleFeatureList

using mrpt::vision::TSimpleFeatureList = typedef TSimpleFeatureList_templ<TSimpleFeature>

A list of image features using the structure TSimpleFeature for each feature.

capable of KD-tree computations

Definition at line 293 of file TSimpleFeature.h.

Function Documentation

◆ detectFeatures_SSE2_FASTER10()

void CFeatureExtraction::detectFeatures_SSE2_FASTER10	(	const mrpt::img::CImage &	img,
		TSimpleFeatureList &	corners,
		const int	threshold = `20`,
		bool	append_to_list = `false`,
		uint8_t	octave = `0`,
		std::vector< size_t > *	out_feats_index_by_row = `nullptr`
	)

static

Just like detectFeatures_SSE2_FASTER9() for another version of the detector.

Definition at line 45 of file CFeatureExtraction_FASTER.cpp.

References ASSERTDEB_, mrpt::vision::TSimpleFeatureList_templ< FEATURE >::clear(), fast_corner_detect_10(), and THROW_EXCEPTION.

◆ detectFeatures_SSE2_FASTER12()

void CFeatureExtraction::detectFeatures_SSE2_FASTER12	(	const mrpt::img::CImage &	img,
		TSimpleFeatureList &	corners,
		const int	threshold = `20`,
		bool	append_to_list = `false`,
		uint8_t	octave = `0`,
		std::vector< size_t > *	out_feats_index_by_row = `nullptr`
	)

static

Just like detectFeatures_SSE2_FASTER9() for another version of the detector.

Definition at line 61 of file CFeatureExtraction_FASTER.cpp.

References ASSERTDEB_, mrpt::vision::TSimpleFeatureList_templ< FEATURE >::clear(), fast_corner_detect_12(), and THROW_EXCEPTION.

Referenced by mrpt::vision::CGenericFeatureTracker::internal_trackFeatures().

◆ detectFeatures_SSE2_FASTER9()

void CFeatureExtraction::detectFeatures_SSE2_FASTER9	(	const mrpt::img::CImage &	img,
		TSimpleFeatureList &	corners,
		const int	threshold = `20`,
		bool	append_to_list = `false`,
		uint8_t	octave = `0`,
		std::vector< size_t > *	out_feats_index_by_row = `nullptr`
	)

static

A SSE2-optimized implementation of FASTER-9 (requires img to be grayscale).

If SSE2 is not available, it gratefully falls back to a non-optimized version.

Only the pt.{x,y} fields are filled out for each feature: the rest of fields are left uninitialized and their content is undefined. Note that (x,y) are already scaled to the 0-level image coordinates if octave>0, by means of:

pt.x = detected.x << octave;

pt.y = detected.y << octave;

If append_to_list is true, the corners list is not cleared before adding the newly detected feats.

If a valid pointer is provided for out_feats_index_by_row, upon return you will find a vector with as many entries as rows in the image (the real number of rows, disregarding the value of octave). The number in each entry is the 0-based index (in corners) of the first feature that falls in that line of the image. This index can be used to fasten looking for correspondences.

Definition at line 29 of file CFeatureExtraction_FASTER.cpp.

References ASSERTDEB_, mrpt::vision::TSimpleFeatureList_templ< FEATURE >::clear(), fast_corner_detect_9(), and THROW_EXCEPTION.

◆ find_descriptor_pairings()

template<class DESCRIPTOR_KDTREE >

size_t mrpt::vision::find_descriptor_pairings	(	std::vector< std::vector< size_t >> *	pairings_1_to_multi_2,
		std::vector< std::pair< size_t, size_t >> *	pairings_1_to_2,
		const CFeatureList &	feats_img1,
		const DESCRIPTOR_KDTREE &	feats_img2_kdtree,
		const mrpt::vision::TDescriptorType	descriptor = `descSIFT`,
		const size_t	max_neighbors = `4`,
		const double	max_relative_distance = `1.2`,
		const typename DESCRIPTOR_KDTREE::kdtree_t::DistanceType	max_distance = `std::numeric_limits< typename DESCRIPTOR_KDTREE::kdtree_t::DistanceType>::max()`
	)

Search for pairings between two sets of visual descriptors (for now, only SURF and SIFT features are considered).

Pairings are returned in one of two formats (or both of them simultaneously), depending on the non-NULL output containers present in the call.

CFeatureList  feats1, feats2;
// Populate feature lists [...]
// Create kd-tree for SIFT features of "feats2":
TSIFTDescriptorsKDTreeIndex<double>  feats2_kdtree(feats2);
// Search correspondences:
std::vector<std::vector<size_t>>             pairings_1_to_multi_2;
std::vector<std::pair<size_t,size_t> > pairings_1_to_2;
mrpt::vision::find_descriptor_pairings(
   &pairings_1_to_multi_2,   // Can be set to nullptr if not needed
   &pairings_1_to_2,         // Can be set to nullptr if not needed
   feats1, feats2_kdtree,    // The two sets of features
   mrpt::vision::descSIFT    // Select descriptor to use
   // [further optional params]
   );

See also: TSIFTDescriptorsKDTreeIndex, TSURFDescriptorsKDTreeIndex

The expected data type of elements for the kd-tree

Definition at line 49 of file descriptor_pairing.h.

References ASSERT_, ASSERT_ABOVEEQ_, ASSERTMSG_, mrpt::vision::descSIFT, mrpt::vision::descSURF, min, MRPT_END, MRPT_START, mrpt::vision::CFeature::TDescriptors::SIFT, mrpt::vision::CFeatureList::size(), mrpt::vision::CFeature::TDescriptors::SURF, and THROW_EXCEPTION.

Detailed Description

Classes

Typedefs

Functions

Static methods with low-level detector functionality

Typedef Documentation

◆ TSimpleFeature

◆ TSimpleFeaturef

◆ TSimpleFeaturefList

◆ TSimpleFeatureList

Function Documentation

◆ detectFeatures_SSE2_FASTER10()

◆ detectFeatures_SSE2_FASTER12()

◆ detectFeatures_SSE2_FASTER9()

◆ find_descriptor_pairings()