Feature Detect in OpenCV

OpenCV v2.3 documentation
http://opencv.itseez.com/index.html
OpenCV Tutorials in OpenCV v2.3 documentation
http://opencv.itseez.com/doc/tutorials/tutorials.html

feature2d module. 2D Features framework
http://opencv.itseez.com/doc/tutorials/features2d/table_of_content_features2d/table_of_content_features2d.html
1. Harris corner detector
http://opencv.itseez.com/doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.html

2. Shi-Tomasi corner detector
http://opencv.itseez.com/doc/tutorials/features2d/trackingmotion/good_features_to_track/good_features_to_track.html

3. Creating yor own corner detector
http://opencv.itseez.com/doc/tutorials/features2d/trackingmotion/generic_corner_detector/generic_corner_detector.html

4. Detecting corners location in subpixeles
http://opencv.itseez.com/doc/tutorials/features2d/trackingmotion/corner_subpixeles/corner_subpixeles.html

5. Feature Detection
http://opencv.itseez.com/doc/tutorials/features2d/feature_detection/feature_detection.html
   1). Use the FeatureDetector interface in order to find interest points. Specifically:
       a) Use the SurfFeatureDetector and its function detect to perform the detection process
       b) Use the function drawKeypoints to draw the detected keypoints
6. Feature Description
http://opencv.itseez.com/doc/tutorials/features2d/feature_description/feature_description.html
   1). Use the DescriptorExtractor interface in order to find the feature vector correspondent to the keypoints. Specifically:
       a) Use SurfDescriptorExtractor and its function compute to perform the required calculations.
       b) Use a BruteForceMatcher to match the features vector
       c) Use the function drawMatches to draw the detected matches.

7. Feature Matching with FLANN
http://opencv.itseez.com/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.html

8. Features2D + Homography to find a known object
http://opencv.itseez.com/doc/tutorials/features2d/feature_homography/feature_homography.html
   1). Use the function findHomography to find the transform between matched keypoints.
   2). Use the function perspectiveTransform to map the points.

9. Detection of planar objects
http://opencv.itseez.com/doc/tutorials/features2d/detection_of_planar_objects/detection_of_planar_objects.html
   1). Create a new console project. Read two input images.
   2). Detect keypoints in both images.
   3). Compute descriptors for each of the keypoints.
   4). Now, find the closest matches between descriptors from the first image to the second:
   5). Visualize the results:
   6). Find the homography transformation between two sets of points:
   7). Create a set of inlier matches and draw them. Use perspectiveTransform function to map points with homography:
   8). Use drawMatches for drawing inliers.