NASA Astrobee Robot Software  0.19.1
Flight software for the Astrobee robots operating inside the International Space Station.
interest_point Namespace Reference

Classes

class  BRISK
 Class implementing the BRISK keypoint detector and descriptor extractor, described in [LCS11] . More...
 
class  BRISK_Impl
 
class  BriskDynamicDetector
 
class  BriskLayer
 
class  BriskScaleSpace
 
class  DynamicDetector
 
class  FeatureDetector
 
class  SurfDynamicDetector
 
class  TeblidDynamicDetector
 

Functions

bool RobustEssential (Eigen::Matrix3d const &k1, Eigen::Matrix3d const &k2, Eigen::Matrix2Xd const &x1, Eigen::Matrix2Xd const &x2, Eigen::Matrix3d *e, std::vector< size_t > *vec_inliers, std::pair< size_t, size_t > const &size1, std::pair< size_t, size_t > const &size2, double *error_max, double precision, const int ransac_iterations=4096)
 
bool EstimateRTFromE (Eigen::Matrix3d const &k1, Eigen::Matrix3d const &k2, Eigen::Matrix2Xd const &x1, Eigen::Matrix2Xd const &x2, Eigen::Matrix3d const &e, std::vector< size_t > const &vec_inliers, Eigen::Matrix3d *r, Eigen::Vector3d *t)
 
void FindMatches (const cv::Mat &img1_descriptor_map, const cv::Mat &img2_descriptor_map, std::vector< cv::DMatch > *matches, boost::optional< int > hamming_distance=boost::none, boost::optional< double > goodness_ratio=boost::none)
 
void makeAgastOffsets (int pixel[16], int rowStride, int type)
 
int agast_tree_search (const uint32_t table_struct32[], int pixel_[], const unsigned char *const ptr, int threshold)
 
int AGAST_ALL_SCORE (const uchar *ptr, const int pixel[], int threshold, int agasttype)
 
template<>
int agast_cornerScore< AgastFeatureDetector::AGAST_5_8 > (const uchar *ptr, const int pixel[], int threshold)
 
template<>
int agast_cornerScore< AgastFeatureDetector::AGAST_7_12d > (const uchar *ptr, const int pixel[], int threshold)
 
template<>
int agast_cornerScore< AgastFeatureDetector::AGAST_7_12s > (const uchar *ptr, const int pixel[], int threshold)
 
template<>
int agast_cornerScore< AgastFeatureDetector::OAST_9_16 > (const uchar *ptr, const int pixel[], int threshold)
 
bool RoiPredicate (const float minX, const float minY, const float maxX, const float maxY, const KeyPoint &keyPt)
 

Function Documentation

◆ AGAST_ALL_SCORE()

int interest_point::AGAST_ALL_SCORE ( const uchar *  ptr,
const int  pixel[],
int  threshold,
int  agasttype 
)

◆ agast_cornerScore< AgastFeatureDetector::AGAST_5_8 >()

template<>
int interest_point::agast_cornerScore< AgastFeatureDetector::AGAST_5_8 > ( const uchar *  ptr,
const int  pixel[],
int  threshold 
)

◆ agast_cornerScore< AgastFeatureDetector::AGAST_7_12d >()

template<>
int interest_point::agast_cornerScore< AgastFeatureDetector::AGAST_7_12d > ( const uchar *  ptr,
const int  pixel[],
int  threshold 
)

◆ agast_cornerScore< AgastFeatureDetector::AGAST_7_12s >()

template<>
int interest_point::agast_cornerScore< AgastFeatureDetector::AGAST_7_12s > ( const uchar *  ptr,
const int  pixel[],
int  threshold 
)

◆ agast_cornerScore< AgastFeatureDetector::OAST_9_16 >()

template<>
int interest_point::agast_cornerScore< AgastFeatureDetector::OAST_9_16 > ( const uchar *  ptr,
const int  pixel[],
int  threshold 
)

◆ agast_tree_search()

int interest_point::agast_tree_search ( const uint32_t  table_struct32[],
int  pixel_[],
const unsigned char *const  ptr,
int  threshold 
)

◆ EstimateRTFromE()

bool interest_point::EstimateRTFromE ( Eigen::Matrix3d const &  k1,
Eigen::Matrix3d const &  k2,
Eigen::Matrix2Xd const &  x1,
Eigen::Matrix2Xd const &  x2,
Eigen::Matrix3d const &  e,
std::vector< size_t > const &  vec_inliers,
Eigen::Matrix3d *  r,
Eigen::Vector3d *  t 
)

◆ FindMatches()

void interest_point::FindMatches ( const cv::Mat &  img1_descriptor_map,
const cv::Mat &  img2_descriptor_map,
std::vector< cv::DMatch > *  matches,
boost::optional< int >  hamming_distance = boost::none,
boost::optional< double >  goodness_ratio = boost::none 
)

descriptor is what opencv descriptor was used to make the descriptors the descriptor maps are the features in the two images matches is output to contain the matching features between the two images Optionally pass hamming distance and goodness ratio, otherwise flag values are used.

◆ makeAgastOffsets()

void interest_point::makeAgastOffsets ( int  pixel[16],
int  rowStride,
int  type 
)

◆ RobustEssential()

bool interest_point::RobustEssential ( Eigen::Matrix3d const &  k1,
Eigen::Matrix3d const &  k2,
Eigen::Matrix2Xd const &  x1,
Eigen::Matrix2Xd const &  x2,
Eigen::Matrix3d *  e,
std::vector< size_t > *  vec_inliers,
std::pair< size_t, size_t > const &  size1,
std::pair< size_t, size_t > const &  size2,
double *  error_max,
double  precision,
const int  ransac_iterations = 4096 
)

◆ RoiPredicate()

bool interest_point::RoiPredicate ( const float  minX,
const float  minY,
const float  maxX,
const float  maxY,
const KeyPoint &  keyPt 
)
inline