OpenCV  3.3.1-dev
Open Source Computer Vision
Modules | Classes | Typedefs | Functions
2D Features Framework

Modules

 Feature Detection and Description
 
 Descriptor Matchers
 
 Drawing Function of Keypoints and Matches
 
 Object Categorization
 

Classes

struct  cv::Accumulator< T >
 
struct  cv::Accumulator< char >
 
struct  cv::Accumulator< short >
 
struct  cv::Accumulator< unsigned char >
 
struct  cv::Accumulator< unsigned short >
 
class  cv::Feature2D
 Abstract base class for 2D image feature detectors and descriptor extractors. More...
 
class  cv::KeyPointsFilter
 A class filters a vector of keypoints. More...
 
struct  cv::L1< T >
 
struct  cv::L2< T >
 
struct  cv::SL2< T >
 

Typedefs

typedef Feature2D cv::DescriptorExtractor
 
typedef Feature2D cv::FeatureDetector
 

Functions

void cv::computeRecallPrecisionCurve (const std::vector< std::vector< DMatch > > &matches1to2, const std::vector< std::vector< uchar > > &correctMatches1to2Mask, std::vector< Point2f > &recallPrecisionCurve)
 
void cv::evaluateFeatureDetector (const Mat &img1, const Mat &img2, const Mat &H1to2, std::vector< KeyPoint > *keypoints1, std::vector< KeyPoint > *keypoints2, float &repeatability, int &correspCount, const Ptr< FeatureDetector > &fdetector=Ptr< FeatureDetector >())
 
int cv::getNearestPoint (const std::vector< Point2f > &recallPrecisionCurve, float l_precision)
 
float cv::getRecall (const std::vector< Point2f > &recallPrecisionCurve, float l_precision)
 

Detailed Description

Typedef Documentation

§ DescriptorExtractor

Extractors of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. This section is devoted to computing descriptors represented as vectors in a multidimensional space. All objects that implement the vector descriptor extractors inherit the DescriptorExtractor interface.

§ FeatureDetector

Feature detectors in OpenCV have wrappers with a common interface that enables you to easily switch between different algorithms solving the same problem. All objects that implement keypoint detectors inherit the FeatureDetector interface.

Function Documentation

§ computeRecallPrecisionCurve()

void cv::computeRecallPrecisionCurve ( const std::vector< std::vector< DMatch > > &  matches1to2,
const std::vector< std::vector< uchar > > &  correctMatches1to2Mask,
std::vector< Point2f > &  recallPrecisionCurve 
)

§ evaluateFeatureDetector()

void cv::evaluateFeatureDetector ( const Mat img1,
const Mat img2,
const Mat H1to2,
std::vector< KeyPoint > *  keypoints1,
std::vector< KeyPoint > *  keypoints2,
float &  repeatability,
int &  correspCount,
const Ptr< FeatureDetector > &  fdetector = PtrFeatureDetector >() 
)

§ getNearestPoint()

int cv::getNearestPoint ( const std::vector< Point2f > &  recallPrecisionCurve,
float  l_precision 
)

§ getRecall()

float cv::getRecall ( const std::vector< Point2f > &  recallPrecisionCurve,
float  l_precision 
)