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Doxygen tutorials: support contrib, some minor changes

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This commit is contained in:
Maksim Shabunin
2014-12-01 19:22:04 +03:00
parent 4ccbd44559
commit d3beb755df
9 changed files with 73 additions and 33 deletions
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2
doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown
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@@ -244,7 +244,7 @@ Here is explained in detail the code for the real time application:
extraction. You can find it in
`samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/src/RobusMatcher.cpp`. In your
*RobusMatch* object you can use any of the 2D features detectors of OpenCV. In this case I used
@ref cv::ORB features because is based on @ref cv::FAST to detect the keypoints and @ref cv::xfeatures2d::BriefDescriptorExtractor
@ref cv::ORB features because is based on @ref cv::FAST to detect the keypoints and cv::xfeatures2d::BriefDescriptorExtractor
to extract the descriptors which means that is fast and robust to rotations. You can find more
detailed information about *ORB* in the documentation.

2
doc/tutorials/features2d/feature_description/feature_description.markdown
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@@ -8,7 +8,7 @@ In this tutorial you will learn how to:
- Use the @ref cv::DescriptorExtractor interface in order to find the feature vector correspondent
to the keypoints. Specifically:
- Use @ref cv::xfeatures2d::SURF and its function @ref cv::xfeatures2d::SURF::compute to perform the
- Use cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::compute to perform the
required calculations.
- Use a @ref cv::BFMatcher to match the features vector
- Use the function @ref cv::drawMatches to draw the detected matches.

2
doc/tutorials/features2d/feature_detection/feature_detection.markdown
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@@ -7,7 +7,7 @@ Goal
In this tutorial you will learn how to:
- Use the @ref cv::FeatureDetector interface in order to find interest points. Specifically:
- Use the @ref cv::xfeatures2d::SURF and its function @ref cv::xfeatures2d::SURF::detect to perform the
- Use the cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::detect to perform the
detection process
- Use the function @ref cv::drawKeypoints to draw the detected keypoints

2
doc/tutorials/video/background_subtraction/background_subtraction.markdown
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@@ -41,7 +41,7 @@ In the following you can find the source code. We will let the user chose to pro
file or a sequence of images.
Two different methods are used to generate two foreground masks:
-# @ref cv::bgsegm::BackgroundSubtractorMOG
-# cv::bgsegm::BackgroundSubtractorMOG
-# @ref cv::BackgroundSubtractorMOG2
The results as well as the input data are shown on the screen.