KLT tracking of features. More...

#include <TrackKLT.h>

Inheritance diagram for ov_core::TrackKLT:

Public Member Functions
void	feed_new_camera (const CameraData &message) override
	Process a new image. More...

	TrackKLT (std::unordered_map< size_t, std::shared_ptr< CamBase >> cameras, int numfeats, int numaruco, bool stereo, HistogramMethod histmethod, int fast_threshold, int gridx, int gridy, int minpxdist)
	Public constructor with configuration variables. More...

Public Member Functions inherited from ov_core::TrackBase
void	change_feat_id (size_t id_old, size_t id_new)
	Changes the ID of an actively tracked feature to another one. More...

virtual void	display_active (cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2, std::string overlay="")
	Shows features extracted in the last image. More...

virtual void	display_history (cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2, std::vector< size_t > highlighted={}, std::string overlay="")
	Shows a "trail" for each feature (i.e. its history) More...

std::shared_ptr< FeatureDatabase >	get_feature_database ()
	Get the feature database with all the track information. More...

std::unordered_map< size_t, std::vector< size_t > >	get_last_ids ()
	Getter method for active features in the last frame (ids per camera) More...

std::unordered_map< size_t, std::vector< cv::KeyPoint > >	get_last_obs ()
	Getter method for active features in the last frame (observations per camera) More...

int	get_num_features ()
	Getter method for number of active features. More...

void	set_num_features (int _num_features)
	Setter method for number of active features. More...

	TrackBase (std::unordered_map< size_t, std::shared_ptr< CamBase >> cameras, int numfeats, int numaruco, bool stereo, HistogramMethod histmethod)
	Public constructor with configuration variables. More...

virtual	~TrackBase ()

Protected Member Functions
void	feed_monocular (const CameraData &message, size_t msg_id)
	Process a new monocular image. More...

void	feed_stereo (const CameraData &message, size_t msg_id_left, size_t msg_id_right)
	Process new stereo pair of images. More...

void	perform_detection_monocular (const std::vector< cv::Mat > &img0pyr, const cv::Mat &mask0, std::vector< cv::KeyPoint > &pts0, std::vector< size_t > &ids0)
	Detects new features in the current image. More...

void	perform_detection_stereo (const std::vector< cv::Mat > &img0pyr, const std::vector< cv::Mat > &img1pyr, const cv::Mat &mask0, const cv::Mat &mask1, size_t cam_id_left, size_t cam_id_right, std::vector< cv::KeyPoint > &pts0, std::vector< cv::KeyPoint > &pts1, std::vector< size_t > &ids0, std::vector< size_t > &ids1)
	Detects new features in the current stereo pair. More...

void	perform_matching (const std::vector< cv::Mat > &img0pyr, const std::vector< cv::Mat > &img1pyr, std::vector< cv::KeyPoint > &pts0, std::vector< cv::KeyPoint > &pts1, size_t id0, size_t id1, std::vector< uchar > &mask_out)
	KLT track between two images, and do RANSAC afterwards. More...

Protected Attributes
int	grid_x

int	grid_y

std::map< size_t, cv::Mat >	img_curr

std::map< size_t, std::vector< cv::Mat > >	img_pyramid_curr

std::map< size_t, std::vector< cv::Mat > >	img_pyramid_last

int	min_px_dist

int	pyr_levels = 5

int	threshold

cv::Size	win_size = cv::Size(15, 15)

Protected Attributes inherited from ov_core::TrackBase
std::unordered_map< size_t, std::shared_ptr< CamBase > >	camera_calib
	Camera object which has all calibration in it. More...

std::map< size_t, bool >	camera_fisheye
	If we are a fisheye model or not. More...

std::atomic< size_t >	currid
	Master ID for this tracker (atomic to allow for multi-threading) More...

std::shared_ptr< FeatureDatabase >	database
	Database with all our current features. More...

HistogramMethod	histogram_method
	What histogram equalization method we should pre-process images with? More...

std::unordered_map< size_t, std::vector< size_t > >	ids_last
	Set of IDs of each current feature in the database. More...

std::map< size_t, cv::Mat >	img_last
	Last set of images (use map so all trackers render in the same order) More...

std::map< size_t, cv::Mat >	img_mask_last
	Last set of images (use map so all trackers render in the same order) More...

std::vector< std::mutex >	mtx_feeds
	Mutexs for our last set of image storage (img_last, pts_last, and ids_last) More...

std::mutex	mtx_last_vars
	Mutex for editing the *_last variables. More...

int	num_features
	Number of features we should try to track frame to frame. More...

std::unordered_map< size_t, std::vector< cv::KeyPoint > >	pts_last
	Last set of tracked points. More...

boost::posix_time::ptime	rT1

boost::posix_time::ptime	rT2

boost::posix_time::ptime	rT3

boost::posix_time::ptime	rT4

boost::posix_time::ptime	rT5

boost::posix_time::ptime	rT6

boost::posix_time::ptime	rT7

bool	use_stereo
	If we should use binocular tracking or stereo tracking for multi-camera. More...

Additional Inherited Members
Public Types inherited from ov_core::TrackBase
enum	HistogramMethod { NONE, HISTOGRAM, CLAHE }
	Desired pre-processing image method. More...

Detailed Description

KLT tracking of features.

This is the implementation of a KLT visual frontend for tracking sparse features. We can track either monocular cameras across time (temporally) along with stereo cameras which we also track across time (temporally) but track from left to right to find the stereo correspondence information also. This uses the calcOpticalFlowPyrLK OpenCV function to do the KLT tracking.

Definition at line 39 of file TrackKLT.h.

Constructor & Destructor Documentation

◆ TrackKLT()

ov_core::TrackKLT::TrackKLT	(	std::unordered_map< size_t, std::shared_ptr< CamBase >>	cameras,
		int	numfeats,
		int	numaruco,
		bool	stereo,
		HistogramMethod	histmethod,
		int	fast_threshold,
		int	gridx,
		int	gridy,
		int	minpxdist
	)

inlineexplicit

Public constructor with configuration variables.

Parameters

cameras	camera calibration object which has all camera intrinsics in it
numfeats	number of features we want want to track (i.e. track 200 points from frame to frame)
numaruco	the max id of the arucotags, so we ensure that we start our non-auroc features above this value
stereo	if we should do stereo feature tracking or binocular
histmethod	what type of histogram pre-processing should be done (histogram eq?)
fast_threshold	FAST detection threshold
gridx	size of grid in the x-direction / u-direction
gridy	size of grid in the y-direction / v-direction
minpxdist	features need to be at least this number pixels away from each other

Definition at line 54 of file TrackKLT.h.

Member Function Documentation

◆ feed_monocular()

void TrackKLT::feed_monocular	(	const CameraData &	message,
		size_t	msg_id
	)

protected

Process a new monocular image.

Parameters

message	Contains our timestamp, images, and camera ids
msg_id	the camera index in message data vector

Definition at line 96 of file TrackKLT.cpp.

◆ feed_new_camera()

void TrackKLT::feed_new_camera ( const CameraData & message )

overridevirtual

Process a new image.

Parameters

message Contains our timestamp, images, and camera ids

Implements ov_core::TrackBase.

Definition at line 34 of file TrackKLT.cpp.

◆ feed_stereo()

void TrackKLT::feed_stereo	(	const CameraData &	message,
		size_t	msg_id_left,
		size_t	msg_id_right
	)

protected

Process new stereo pair of images.

Parameters

message	Contains our timestamp, images, and camera ids
msg_id_left	first image index in message data vector
msg_id_right	second image index in message data vector

Definition at line 202 of file TrackKLT.cpp.

◆ perform_detection_monocular()

void TrackKLT::perform_detection_monocular	(	const std::vector< cv::Mat > &	img0pyr,
		const cv::Mat &	mask0,
		std::vector< cv::KeyPoint > &	pts0,
		std::vector< size_t > &	ids0
	)

protected

Detects new features in the current image.

Parameters

img0pyr	image we will detect features on (first level of pyramid)
mask0	mask which has what ROI we do not want features in
pts0	vector of currently extracted keypoints in this image
ids0	vector of feature ids for each currently extracted keypoint

Given an image and its currently extracted features, this will try to add new features if needed. Will try to always have the "max_features" being tracked through KLT at each timestep. Passed images should already be grayscaled.

Definition at line 395 of file TrackKLT.cpp.

◆ perform_detection_stereo()

void TrackKLT::perform_detection_stereo	(	const std::vector< cv::Mat > &	img0pyr,
		const std::vector< cv::Mat > &	img1pyr,
		const cv::Mat &	mask0,
		const cv::Mat &	mask1,
		size_t	cam_id_left,
		size_t	cam_id_right,
		std::vector< cv::KeyPoint > &	pts0,
		std::vector< cv::KeyPoint > &	pts1,
		std::vector< size_t > &	ids0,
		std::vector< size_t > &	ids1
	)

protected

Detects new features in the current stereo pair.

Parameters

img0pyr	left image we will detect features on (first level of pyramid)
img1pyr	right image we will detect features on (first level of pyramid)
mask0	mask which has what ROI we do not want features in
mask1	mask which has what ROI we do not want features in
cam_id_left	first camera sensor id
cam_id_right	second camera sensor id
pts0	left vector of currently extracted keypoints
pts1	right vector of currently extracted keypoints
ids0	left vector of feature ids for each currently extracted keypoint
ids1	right vector of feature ids for each currently extracted keypoint

This does the same logic as the perform_detection_monocular() function, but we also enforce stereo contraints. So we detect features in the left image, and then KLT track them onto the right image. If we have valid tracks, then we have both the keypoint on the left and its matching point in the right image. Will try to always have the "max_features" being tracked through KLT at each timestep.

Definition at line 530 of file TrackKLT.cpp.

◆ perform_matching()

void TrackKLT::perform_matching	(	const std::vector< cv::Mat > &	img0pyr,
		const std::vector< cv::Mat > &	img1pyr,
		std::vector< cv::KeyPoint > &	pts0,
		std::vector< cv::KeyPoint > &	pts1,
		size_t	id0,
		size_t	id1,
		std::vector< uchar > &	mask_out
	)

protected

KLT track between two images, and do RANSAC afterwards.

Parameters

img0pyr	starting image pyramid
img1pyr	image pyramid we want to track too
pts0	starting points
pts1	points we have tracked
id0	id of the first camera
id1	id of the second camera
mask_out	what points had valid tracks

This will track features from the first image into the second image. The two point vectors will be of equal size, but the mask_out variable will specify which points are good or bad. If the second vector is non-empty, it will be used as an initial guess of where the keypoints are in the second image.

Definition at line 829 of file TrackKLT.cpp.

Member Data Documentation

◆ grid_x

int ov_core::TrackKLT::grid_x

protected

Definition at line 136 of file TrackKLT.h.

◆ grid_y

int ov_core::TrackKLT::grid_y

protected

Definition at line 137 of file TrackKLT.h.

◆ img_curr

std::map<size_t, cv::Mat> ov_core::TrackKLT::img_curr

protected

Definition at line 148 of file TrackKLT.h.

◆ img_pyramid_curr

std::map<size_t, std::vector<cv::Mat> > ov_core::TrackKLT::img_pyramid_curr

protected

Definition at line 149 of file TrackKLT.h.

◆ img_pyramid_last

std::map<size_t, std::vector<cv::Mat> > ov_core::TrackKLT::img_pyramid_last

protected

Definition at line 147 of file TrackKLT.h.

◆ min_px_dist

int ov_core::TrackKLT::min_px_dist

protected

Definition at line 140 of file TrackKLT.h.

◆ pyr_levels

int ov_core::TrackKLT::pyr_levels = 5

protected

Definition at line 143 of file TrackKLT.h.

◆ threshold

int ov_core::TrackKLT::threshold

protected

Definition at line 135 of file TrackKLT.h.

◆ win_size

cv::Size ov_core::TrackKLT::win_size = cv::Size(15, 15)

protected

Definition at line 144 of file TrackKLT.h.

The documentation for this class was generated from the following files:

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ TrackKLT()

Member Function Documentation

◆ feed_monocular()

◆ feed_new_camera()

◆ feed_stereo()

◆ perform_detection_monocular()

◆ perform_detection_stereo()

◆ perform_matching()

Member Data Documentation

◆ grid_x

◆ grid_y

◆ img_curr

◆ img_pyramid_curr

◆ img_pyramid_last

◆ min_px_dist

◆ pyr_levels

◆ threshold

◆ win_size