find_camera_mtx.md

@@ -10,11 +10,11 @@ We are looking for the Camera Matrix **K** and Distortion Coefficients **D** des
 
 where ![alt text](http://mathurl.com/zbyrpbe.png) are camera focal lengths, ![alt text](http://mathurl.com/jchq2he.png) are optical centers, *p* and *k* are distortion coefficients. 
 
-### Calibration object
-We chose classic black-white chessboard pattern with 8 rows, 7 columns and square's size approximately 35x35mm (Exact dimensions are specified in source code) as a calibration object.
+### Calibration pattern
+We chose classic black-white chessboard pattern with eight rows, seven columns and square's size approximately 35x35mm (Exact dimensions are specified in source code) as a calibration object.
 
 ### Calibration pictures
-We must take pictures with calibration object in the camera's Field of View (FoV) in many different positions to cover most of FoV. Moreover, we must respect that the whole chessboard must be visible.
+We must take pictures with calibration object in the camera's Field of View (FoV) in many different positions to cover most of the FoV. Moreover, we must respect that the whole chessboard must be visible.
 
 ### Finding chessboards
 We use OpenCV function `findChessboarCorners(gray,(rows,column),params=None)->ret,corners` for finding the chessboard in pictures, where `corners` are chessboard's internal corners in pixel (u,v) coordinates. After the chessboard is found, the position of corners is made more precise via OpenCV `cornerSubPixel(gray,corners,winSize,zeroZone,criteria)->None`, which finds them with sub-pixel precision. You can read more about this on the page listed above.
@@ -22,8 +22,9 @@ We use OpenCV function `findChessboarCorners(gray,(rows,column),params=None)->re
 ### Camera Matrix and Distortion Coefficients
 When we know the position of chessboards in pictures (imagePoints) and correct size of squares and its positions (objectPoints), we can now estimate the Camera Matrix and Distortion Coefficients with OpenCV function `calibrateCamera(objectPoints,imagePoints,imageShape,None,None)->ret,cam_mtx,dist,rvect,tvect`, where `cam_mtx` is the wanted Camera Matrix and `dist` are Distortion coefficients.
 
-
-
+### ChAruCo callibration pattern
+ 
+The calibration using ChAruCo can be initialized using `CameraCalibrationLiveCharuco`. The parameters of a board must be specified inside the script. The package `Calibration.CharucoCameraCalibration` creates the board using `generate_charuco_board(dict, rows, columns, square length, marker length)`, where dict is an OpenCV3 AruCo dictionary, the rest is a shape of board and size of squares in meters.
 
 
    
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