Add next and previous navigation links to all tutorials

doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown

@@ -1,6 +1,10 @@
 Camera calibration With OpenCV {#tutorial_camera_calibration}
 ==============================
 
+@prev_tutorial{tutorial_camera_calibration_square_chess}
+@next_tutorial{tutorial_real_time_pose}
+
+
 Cameras have been around for a long-long time. However, with the introduction of the cheap *pinhole*
 cameras in the late 20th century, they became a common occurrence in our everyday life.
 Unfortunately, this cheapness comes with its price: significant distortion. Luckily, these are

doc/tutorials/calib3d/camera_calibration_pattern/camera_calibration_pattern.markdown

@@ -1,6 +1,9 @@
 Create calibration pattern {#tutorial_camera_calibration_pattern}
 =========================================
 
+@next_tutorial{tutorial_camera_calibration_square_chess}
+
+
 The goal of this tutorial is to learn how to create calibration pattern.
 
 You can find a chessboard pattern in https://github.com/opencv/opencv/blob/3.4/doc/pattern.png

doc/tutorials/calib3d/camera_calibration_square_chess/camera_calibration_square_chess.markdown

@@ -1,6 +1,10 @@
 Camera calibration with square chessboard {#tutorial_camera_calibration_square_chess}
 =========================================
 
+@prev_tutorial{tutorial_camera_calibration_pattern}
+@next_tutorial{tutorial_camera_calibration}
+
+
 The goal of this tutorial is to learn how to calibrate a camera given a set of chessboard images.
 
 *Test data*: use images in your data/chess folder.

doc/tutorials/calib3d/interactive_calibration/interactive_calibration.markdown

@@ -1,6 +1,9 @@
 Interactive camera calibration application {#tutorial_interactive_calibration}
 ==============================
 
+@prev_tutorial{tutorial_real_time_pose}
+
+
 According to classical calibration technique user must collect all data first and when run @ref cv::calibrateCamera function
 to obtain camera parameters. If average re-projection error is huge or if estimated parameters seems to be wrong, process of
 selection or collecting data and starting of @ref cv::calibrateCamera repeats.

doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown

@@ -1,6 +1,10 @@
 Real Time pose estimation of a textured object {#tutorial_real_time_pose}
 ==============================================
 
+@prev_tutorial{tutorial_camera_calibration}
+@next_tutorial{tutorial_interactive_calibration}
+
+
 Nowadays, augmented reality is one of the top research topic in computer vision and robotics fields.
 The most elemental problem in augmented reality is the estimation of the camera pose respect of an
 object in the case of computer vision area to do later some 3D rendering or in the case of robotics