问题
I'm trying to get started working with sift feature extraction using (C++) OpenCv. I need to extract features using SIFT, match them between the original image (e.g. a book) and a scene, and after that calculate the camera pose.
So far I have found this algorithm using SURF. Does anyone know a base code from which I can get started, or maybe a way to convert the algorithm in the link from SURF to SIFT?
Thanks in advance.
EDIT: Ok, I worked out a solution for the sift problem. Now I'm trying to figure the camera pose. I'm trying to use: solvePnP, can anyone help me with an example?
回答1:
Check out the feature2d tutorial section of the new OpenCV docs website. There tutorials with code showing:
- Feature detection with e.g. SURF
- Feature Description
- Feature Matching
回答2:
If you have managed to find matches between the image and the scene, then I suggest you apply cv::findHomography(). It will calculate the homography matrix using 4 matches as input.
You can convert to camera pose from the homography matrix directly.
回答3:
For using SIFT instead of SURF, I changed SurfFeatureDetector to SiftFeatureDetector and SurfDescriptorExtractor to SiftDescriptorExtractor. For some images, I found that the combination SURF detector <--> SIFT descriptor yields relatively accurate results, but you should experiment with other combinations (FAST detector - FREAK descriptor or ORB detector - BRISK descriptor), depending on your requirements.
Please follow this tutorial for solving the homography part of your question: Feature Matching and Homography
Also, maybe this will help: Pose Estimation
来源：https://stackoverflow.com/questions/11378203/sift-extraction-opencv