surf

I am learning OpenCV and have started exploring the SURF Algorithm for image matching. I have created a sample image library by modifying the default images available with Microsoft Windows 7. Each image has a rotated, scaled, blurred and skewed version in the same folder. My code for finding out matching images is as shown below. As can be seen in the code, the distance is measured by the line dis/objectDescriptors->total and further similarity is calculated by 100 - (dis/objectDescriptors->total) *100 . Unfortunately, this is giving me some weird false positives. For example, it matches the

I have a question about objects matching with OpenCV. I'm useing SURF algorithm implemented in opencv 2.3 to first detect features on each image, and then extracting the descriptors of these features. The problem in matching using Brute Force Matcher, I don't know how I judge that the two images are matched or not that's as when I'm using two different images there are lines between descriptors in the two images! These outputs of my code, either the two images -I compare with them - are similar or different, the result image indicate that the two images are matched. The question is: How can I

I'm using OpenCV 2.3 for keypoints detection and matching. But I am a bit confused with the size and response parameters given by the detection algorithm. What do they exactly mean? Based on the OpenCV manual, I can't figure it out: float size : diameter of the meaningful keypoint neighborhood float response : the response by which the most strong keypoints have been selected. Can be used for further sorting or subsampling I thought the best point to track would be the one with the highest response but it seems that it is not the case. So how could I subsample the set of key points returned by

When using OpenCV for example, algorithms like SIFT or SURF are often used to detect keypoints. My question is what actually are these keypoints? I understand that they are some kind of "points of interest" in an image. I also know that they are scale invariant and are circular. Also, I found out that they have orientation but I couldn't understand what this actually is. Is it an angle but between the radius and something? Can you give some explanation? I think I need what I need first is something simpler and after that it will be easier to understand the papers. Those are some very good

When I try to run the sample find_obj.cpp or any OpenCV SURF program I get the following error in command prompt while executing the code. The project builds without errors and warnings. I am using VS2011 beta, OpenCV 2.4 and windows7. Error message: OpenCV Error: The function/feature is not implemented < OpenCV was built without SURF support> in unknown function,file ..\..\..\src\opencv\modules\legacy\src\features2d.cpp, line 77 I tried to build the OpenCV 2.4 again using Cmake and then VS2011 in debug mode and then added the lib paths in the IDE, but still no result. How can I fix that?