Delphi-OpenCV/source/ocv.tracking_c.pas

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(*
**************************************************************************************************
Project Delphi-OpenCV
**************************************************************************************************
Contributor:
Laentir Valetov
email:laex@bk.ru
Mikhail Grigorev
email:sleuthound@gmail.com
**************************************************************************************************
You may retrieve the latest version of this file at the GitHub,
located at git://github.com/Laex/Delphi-OpenCV.git
**************************************************************************************************
License:
The contents of this file are subject to the Mozilla Public License Version 1.1 (the "License");
you may not use this file except in compliance with the License. You may obtain a copy of the
License at http://www.mozilla.org/MPL/
Software distributed under the License is distributed on an "AS IS" basis, WITHOUT WARRANTY OF
ANY KIND, either express or implied. See the License for the specific language governing rights
and limitations under the License.
Alternatively, the contents of this file may be used under the terms of the
GNU Lesser General Public License (the "LGPL License"), in which case the
provisions of the LGPL License are applicable instead of those above.
If you wish to allow use of your version of this file only under the terms
of the LGPL License and not to allow others to use your version of this file
under the MPL, indicate your decision by deleting the provisions above and
replace them with the notice and other provisions required by the LGPL
License. If you do not delete the provisions above, a recipient may use
your version of this file under either the MPL or the LGPL License.
For more information about the LGPL: http://www.gnu.org/copyleft/lesser.html
**************************************************************************************************
Warning: Using Delphi XE3 syntax!
**************************************************************************************************
The Initial Developer of the Original Code:
OpenCV: open source computer vision library
Homepage: http://ocv.org
Online docs: http://docs.ocv.org
Q&A forum: http://answers.ocv.org
Dev zone: http://code.ocv.org
**************************************************************************************************
Original file:
opencv\modules\video\include\opencv2\video\tracking_c.h
*************************************************************************************************
*)
unit ocv.tracking_c;
{$I OpenCV.inc}
interface
uses ocv.core.types_c, ocv.imgproc.types_c;
(* ****************************************************************************************
* Motion Analysis *
*************************************************************************************** *)
// ************************************ optical flow ***************************************
const
CV_LKFLOW_PYR_A_READY = 1;
CV_LKFLOW_PYR_B_READY = 2;
CV_LKFLOW_INITIAL_GUESSES = 4;
CV_LKFLOW_GET_MIN_EIGENVALS = 8;
(*
It is Lucas & Kanade method, modified to use pyramids.
Also it does several iterations to get optical flow for
every point at every pyramid level.
Calculates optical flow between two images for certain set of points (i.e.
it is a "sparse" optical flow, which is opposite to the previous 3 methods)
CVAPI(void) cvCalcOpticalFlowPyrLK( const CvArr* prev, const CvArr* curr,
CvArr* prev_pyr, CvArr* curr_pyr,
const CvPoint2D32f* prev_features,
CvPoint2D32f* curr_features,
int count,
CvSize win_size,
int level,
char* status,
float* track_error,
CvTermCriteria criteria,
int flags );
*)
{$IFDEF SAFELOADLIB}
Type
TcvCalcOpticalFlowPyrLK = procedure(const prev: pIplImage; const curr: pIplImage; prev_pyr: pIplImage; curr_pyr: pIplImage;
const prev_features: pCvPoint2D32f; curr_features: pCvPoint2D32f; count: Integer; win_size: TCvSize; level: Integer; status: pCVChar;
track_error: PSingle; criteria: TCvTermCriteria; flags: Integer); cdecl;
Var
cvCalcOpticalFlowPyrLK: TcvCalcOpticalFlowPyrLK;
{$ELSE}
{$EXTERNALSYM cvCalcOpticalFlowPyrLK}
procedure cvCalcOpticalFlowPyrLK(const prev: pIplImage; const curr: pIplImage; prev_pyr: pIplImage; curr_pyr: pIplImage;
const prev_features: pCvPoint2D32f; curr_features: pCvPoint2D32f; count: Integer; win_size: TCvSize; level: Integer; status: pCVChar;
track_error: PSingle; criteria: TCvTermCriteria; flags: Integer); cdecl;
{$ENDIF}
(* Modification of a previous sparse optical flow algorithm to calculate
affine flow
CVAPI(void) cvCalcAffineFlowPyrLK( const CvArr* prev, const CvArr* curr,
CvArr* prev_pyr, CvArr* curr_pyr,
const CvPoint2D32f* prev_features,
CvPoint2D32f* curr_features,
float* matrices, int count,
CvSize win_size, int level,
char* status, float* track_error,
CvTermCriteria criteria, int flags );
*)
{$IFDEF SAFELOADLIB}
Type
TcvCalcAffineFlowPyrLK = procedure(const prev: pCvArr; const curr: pCvArr; prev_pyr: pCvArr; curr_pyr: pCvArr; const prev_features: pCvPoint2D32f;
var curr_features: TCvPoint2D32f; var matrices: Single; count: Integer; win_size: TCvSize; level: Integer; status: pCVChar;
var track_error: Single; criteria: TCvTermCriteria; flags: Integer); cdecl;
Var
cvCalcAffineFlowPyrLK: TcvCalcAffineFlowPyrLK;
{$ELSE}
{$EXTERNALSYM cvCalcAffineFlowPyrLK}
procedure cvCalcAffineFlowPyrLK(const prev: pCvArr; const curr: pCvArr; prev_pyr: pCvArr; curr_pyr: pCvArr; const prev_features: pCvPoint2D32f;
var curr_features: TCvPoint2D32f; var matrices: Single; count: Integer; win_size: TCvSize; level: Integer; status: pCVChar; var track_error: Single;
criteria: TCvTermCriteria; flags: Integer); cdecl;
{$ENDIF}
(*
Estimate rigid transformation between 2 images or 2 point sets
CVAPI(int) cvEstimateRigidTransform( const CvArr* A, const CvArr* B,
CvMat* M, int full_affine );
*)
{$IFDEF SAFELOADLIB}
Type
TcvEstimateRigidTransform = function(const A: pCvArr; const B: pCvArr; var M: TCvMat; full_affine: Integer): Integer; cdecl;
var
cvEstimateRigidTransform: TcvEstimateRigidTransform;
{$ELSE}
{$EXTERNALSYM cvEstimateRigidTransform}
function cvEstimateRigidTransform(const A: pCvArr; const B: pCvArr; var M: TCvMat; full_affine: Integer): Integer; cdecl;
{$ENDIF}
(*
Estimate optical flow for each pixel using the two-frame G. Farneback algorithm
CVAPI(void) cvCalcOpticalFlowFarneback( const CvArr* prev, const CvArr* next,
CvArr* flow, double pyr_scale, int levels,
int winsize, int iterations, int poly_n,
double poly_sigma, int flags );
*)
{$IFDEF SAFELOADLIB}
type
TcvCalcOpticalFlowFarneback = procedure(const prev: pCvMat; const next: pCvMat; flow: pCvMat; pyr_scale: double; levels: Integer; winsize: Integer;
iterations: Integer; poly_n: Integer; poly_sigma: double; flags: Integer); cdecl;
var
cvCalcOpticalFlowFarneback: TcvCalcOpticalFlowFarneback;
{$ELSE}
{$EXTERNALSYM cvCalcOpticalFlowFarneback}
procedure cvCalcOpticalFlowFarneback(const prev: pCvMat; const next: pCvMat; flow: pCvMat; pyr_scale: double; levels: Integer; winsize: Integer;
iterations: Integer; poly_n: Integer; poly_sigma: double; flags: Integer); cdecl;
{$ENDIF}
(* ******************************** motion templates ************************************ *)
(* *****************************************************************************************
* All the motion template functions work only with single channel images. *
* Silhouette image must have depth IPL_DEPTH_8U or IPL_DEPTH_8S *
* Motion history image must have depth IPL_DEPTH_32F, *
* Gradient mask - IPL_DEPTH_8U or IPL_DEPTH_8S, *
* Motion orientation image - IPL_DEPTH_32F *
* Segmentation mask - IPL_DEPTH_32F *
* All the angles are in degrees, all the times are in milliseconds *
*************************************************************************************** *)
(*
Updates motion history image given motion silhouette
CVAPI(void) cvUpdateMotionHistory( const CvArr* silhouette, CvArr* mhi,
double timestamp, double duration );
*)
{$IFDEF SAFELOADLIB}
Type
TcvUpdateMotionHistory = procedure(const silhouette: pCvArr; mhi: pCvArr; timestamp: double; duration: double); cdecl;
var
cvUpdateMotionHistory: TcvUpdateMotionHistory;
{$ELSE}
{$EXTERNALSYM cvUpdateMotionHistory}
procedure cvUpdateMotionHistory(const silhouette: pCvArr; mhi: pCvArr; timestamp: double; duration: double); cdecl;
{$ENDIF}
(*
Calculates gradient of the motion history image and fills
a mask indicating where the gradient is valid
CVAPI(void) cvCalcMotionGradient( const CvArr* mhi, CvArr* mask, CvArr* orientation,
double delta1, double delta2,
int aperture_size CV_DEFAULT(3));
*)
{$IFDEF SAFELOADLIB}
Type
TcvCalcMotionGradient = procedure(const mhi: pCvArr; mask: pCvArr; orientation: pCvArr; delta1: double; delta2: double;
aperture_size: Integer = 3); cdecl;
var
cvCalcMotionGradient: TcvCalcMotionGradient;
{$ELSE}
{$EXTERNALSYM cvCalcMotionGradient}
procedure cvCalcMotionGradient(const mhi: pCvArr; mask: pCvArr; orientation: pCvArr; delta1: double; delta2: double;
aperture_size: Integer = 3); cdecl;
{$ENDIF}
(* Calculates average motion direction within a selected motion region
(region can be selected by setting ROIs and/or by composing a valid gradient mask
with the region mask)
CVAPI(double) cvCalcGlobalOrientation( const CvArr* orientation, const CvArr* mask,
const CvArr* mhi, double timestamp,
double duration );
*)
{$IFDEF SAFELOADLIB}
type
TcvCalcGlobalOrientation = function(const orientation: pCvArr; const mask: pCvArr; const mhi: pCvArr; timestamp: double; duration: double)
: double; cdecl;
var
cvCalcGlobalOrientation: TcvCalcGlobalOrientation;
{$ELSE}
{$EXTERNALSYM cvCalcGlobalOrientation}
function cvCalcGlobalOrientation(const orientation: pCvArr; const mask: pCvArr; const mhi: pCvArr; timestamp: double; duration: double)
: double; cdecl;
{$ENDIF}
(* Splits a motion history image into a few parts corresponding to separate independent motions
(e.g. left hand, right hand)
CVAPI(CvSeq* ) cvSegmentMotion( const CvArr* mhi, CvArr* seg_mask,
CvMemStorage* storage,
double timestamp, double seg_thresh );
*)
{$IFDEF SAFELOADLIB}
type
TcvSegmentMotion = function(const mhi: pCvArr; seg_mask: pCvArr; storage: pCvMemStorage; timestamp: double; seg_thresh: double): pCvSeq; cdecl;
var
cvSegmentMotion: TcvSegmentMotion;
{$ELSE}
{$EXTERNALSYM cvSegmentMotion}
function cvSegmentMotion(const mhi: pCvArr; seg_mask: pCvArr; storage: pCvMemStorage; timestamp: double; seg_thresh: double): pCvSeq; cdecl;
{$ENDIF}
(* ****************************************************************************************
* Tracking *
*************************************************************************************** *)
(*
Implements CAMSHIFT algorithm - determines object position, size and orientation
from the object histogram back project (extension of meanshift)
CVAPI(int) cvCamShift( const CvArr* prob_image, CvRect window,
CvTermCriteria criteria, CvConnectedComp* comp,
CvBox2D* box CV_DEFAULT(NULL) );
*)
{$IFDEF SAFELOADLIB}
type
TcvCamShift = function(const prob_image: pIplImage; window: TCvRect; criteria: TCvTermCriteria; comp: pCvConnectedComp; box: pCvBox2D = nil)
: Integer; cdecl;
var
cvCamShift: TcvCamShift;
{$ELSE}
{$EXTERNALSYM cvCamShift}
function cvCamShift(const prob_image: pIplImage; window: TCvRect; criteria: TCvTermCriteria; comp: pCvConnectedComp; box: pCvBox2D = nil)
: Integer; cdecl;
{$ENDIF}
(* Implements MeanShift algorithm - determines object position
from the object histogram back project
CVAPI(int) cvMeanShift( const CvArr* prob_image, CvRect window,
CvTermCriteria criteria, CvConnectedComp* comp );
*)
{$IFDEF SAFELOADLIB}
type
TcvMeanShift = function(const prob_image: pCvArr; window: TCvRect; criteria: TCvTermCriteria; var comp: TCvConnectedComp): Integer; cdecl;
var
cvMeanShift: TcvMeanShift;
{$ELSE}
{$EXTERNALSYM cvMeanShift}
function cvMeanShift(const prob_image: pCvArr; window: TCvRect; criteria: TCvTermCriteria; var comp: TCvConnectedComp): Integer; cdecl;
{$ENDIF}
(*
standard Kalman filter (in G. Welch' and G. Bishop's notation):
x(k)=A*x(k-1)+B*u(k)+w(k) p(w)~N(0,Q)
z(k)=H*x(k)+v(k), p(v)~N(0,R)
*)
Type
pCvKalman = ^TCvKalman;
{$EXTERNALSYM TCvKalman}
TCvKalman = record
MP: Integer; (* number of measurement vector dimensions *)
DP: Integer; (* number of state vector dimensions *)
CP: Integer; (* number of control vector dimensions *)
(* backward compatibility fields *)
// {$IFDEF 1}
PosterState: PSingle; (* =state_pre->data.fl *)
PriorState: PSingle; (* =state_post->data.fl *)
DynamMatr: PSingle; (* =transition_matrix->data.fl *)
MeasurementMatr: PSingle; (* =measurement_matrix->data.fl *)
MNCovariance: PSingle; (* =measurement_noise_cov->data.fl *)
PNCovariance: PSingle; (* =process_noise_cov->data.fl *)
KalmGainMatr: PSingle; (* =gain->data.fl *)
PriorErrorCovariance: PSingle; (* =error_cov_pre->data.fl *)
PosterErrorCovariance: PSingle; (* =error_cov_post->data.fl *)
_Temp1: PSingle; (* temp1->data.fl *)
_Temp2: PSingle; (* temp2->data.fl *)
// {$ENDIF}
state_pre: pCvMat; (* predicted state (x'(k)):
x(k)=A*x(k-1)+B*u(k) *)
state_post: pCvMat; (* corrected state (x(k)):
x(k)=x'(k)+K(k)*(z(k)-H*x'(k)) *)
transition_matrix: pCvMat; (* state transition matrix (A) *)
control_matrix: pCvMat; (* control matrix (B)
(it is not used if there is no control) *)
measurement_matrix: pCvMat; (* measurement matrix (H) *)
process_noise_cov: pCvMat; (* process noise covariance matrix (Q) *)
measurement_noise_cov: pCvMat; (* measurement noise covariance matrix (R) *)
error_cov_pre: pCvMat; (* priori error estimate covariance matrix (P'(k)):
P'(k)=A*P(k-1)*At + Q) *)
gain: pCvMat; (* Kalman gain matrix (K(k)):
K(k)=P'(k)*Ht*inv(H*P'(k)*Ht+R) *)
error_cov_post: pCvMat; (* posteriori error estimate covariance matrix (P(k)):
P(k)=(I-K(k)*H)*P'(k) *)
Temp1: pCvMat; (* temporary matrices *)
Temp2: pCvMat;
temp3: pCvMat;
temp4: pCvMat;
temp5: pCvMat;
end;
//
(*
Creates Kalman filter and sets A, B, Q, R and state to some initial values
CVAPI(CvKalman* ) cvCreateKalman( int dynam_params, int measure_params,
int control_params CV_DEFAULT(0));
*)
{$IFDEF SAFELOADLIB}
type
TcvCreateKalman = function(dynam_params: Integer; measure_params: Integer; control_params: Integer = 0): pCvKalman; cdecl;
var
cvCreateKalman: TcvCreateKalman;
{$ELSE}
{$EXTERNALSYM cvCreateKalman}
function cvCreateKalman(dynam_params: Integer; measure_params: Integer; control_params: Integer = 0): pCvKalman; cdecl;
{$ENDIF}
(*
Releases Kalman filter state
CVAPI(void) cvReleaseKalman( CvKalman** kalman);
*)
{$IFDEF SAFELOADLIB}
type
TcvReleaseKalman = procedure(var kalman: pCvKalman); cdecl;
var
cvReleaseKalman: TcvReleaseKalman;
{$ELSE}
{$EXTERNALSYM cvReleaseKalman}
procedure cvReleaseKalman(var kalman: pCvKalman); cdecl;
{$ENDIF}
(*
Updates Kalman filter by time (predicts future state of the system)
CVAPI(const CvMat* cvKalmanPredict( CvKalman* kalman,
const CvMat* control CV_DEFAULT(NULL));
Updates Kalman filter by measurement
(corrects state of the system and internal matrices)
CVAPI(const CvMat* ) cvKalmanCorrect( CvKalman* kalman, const CvMat* measurement );
*)
type
TcvKalmanPredict = function(var kalman: TCvKalman; const control: pCvMat = nil): pCvMat; cdecl;
TcvKalmanCorrect = function(var kalman: TCvKalman; const measurement: pCvMat): pCvMat; cdecl;
{$IFDEF SAFELOADLIB}
var
cvKalmanPredict: TcvKalmanPredict;
cvKalmanCorrect: TcvKalmanCorrect;
{$ELSE}
{$EXTERNALSYM cvKalmanPredict}
function cvKalmanPredict(var kalman: TCvKalman; const control: pCvMat = nil): pCvMat; cdecl;
{$EXTERNALSYM cvKalmanCorrect}
function cvKalmanCorrect(var kalman: TCvKalman; const measurement: pCvMat): pCvMat; cdecl;
{$ENDIF}
Var
{$EXTERNALSYM cvKalmanUpdateByTime}
cvKalmanUpdateByTime: TcvKalmanPredict {$IFNDEF SAFELOADLIB} = cvKalmanPredict {$ENDIF};
{$EXTERNALSYM cvKalmanUpdateByMeasurement}
cvKalmanUpdateByMeasurement: TcvKalmanCorrect{$IFNDEF SAFELOADLIB} = cvKalmanCorrect{$ENDIF};
{$IF DEFINED(SAFELOADLIB) AND DEFINED(DEBUG)}
procedure Init_opencv_Tracking_lib;
{$ENDIF}
implementation
uses
ocv.lib;
{$IFDEF SAFELOADLIB}
Var
TrackingDLL: Cardinal;
procedure Init_opencv_Tracking_lib;
begin
TrackingDLL := ocvLoadLibrary(tracking_lib);
Assert(TrackingDLL <> 0, 'Can not init ' + tracking_lib);
cvCalcOpticalFlowPyrLK := ocvGetProcAddress('cvCalcOpticalFlowPyrLK', TrackingDLL);
cvCalcAffineFlowPyrLK := ocvGetProcAddress('cvCalcAffineFlowPyrLK', TrackingDLL);
cvEstimateRigidTransform := ocvGetProcAddress('cvEstimateRigidTransform', TrackingDLL);
cvCalcOpticalFlowFarneback := ocvGetProcAddress('cvCalcOpticalFlowFarneback', TrackingDLL);
cvUpdateMotionHistory := ocvGetProcAddress('cvUpdateMotionHistory', TrackingDLL);
cvCalcMotionGradient := ocvGetProcAddress('cvCalcMotionGradient', TrackingDLL);
cvCalcGlobalOrientation := ocvGetProcAddress('cvCalcGlobalOrientation', TrackingDLL);
cvSegmentMotion := ocvGetProcAddress('cvSegmentMotion', TrackingDLL);
cvCamShift := ocvGetProcAddress('cvCamShift', TrackingDLL);
cvMeanShift := ocvGetProcAddress('cvMeanShift', TrackingDLL);
cvCreateKalman := ocvGetProcAddress('cvCreateKalman', TrackingDLL);
cvReleaseKalman := ocvGetProcAddress('cvReleaseKalman', TrackingDLL);
cvKalmanPredict := ocvGetProcAddress('cvKalmanPredict', TrackingDLL);
cvKalmanCorrect := ocvGetProcAddress('cvKalmanCorrect', TrackingDLL);
cvKalmanUpdateByTime := cvKalmanPredict;
cvKalmanUpdateByMeasurement := cvKalmanCorrect;
end;
initialization
Init_opencv_Tracking_lib;
{$ELSE}
function cvCamShift; external tracking_lib;
procedure cvCalcOpticalFlowPyrLK; external tracking_lib;
procedure cvCalcOpticalFlowFarneback; external tracking_lib;
procedure cvUpdateMotionHistory; external tracking_lib;
procedure cvCalcMotionGradient; external tracking_lib;
function cvSegmentMotion; external tracking_lib;
function cvCalcGlobalOrientation; external tracking_lib;
procedure cvCalcAffineFlowPyrLK; external tracking_lib;
function cvEstimateRigidTransform; external tracking_lib;
function cvMeanShift; external tracking_lib;
function cvCreateKalman; external tracking_lib;
function cvKalmanPredict; external tracking_lib;
function cvKalmanCorrect; external tracking_lib;
procedure cvReleaseKalman; external tracking_lib;
{$ENDIF}
end.