FEATURE MATCHING for AUTOSTITCHING

1. Detecting corner features in an image:

Here are the results of using the Harris Interest Point Detector on my images.

Adaptive Non-Maximal Suppression results:

2. Extracting a Feature Descriptor for each feature point :

In order to extract feature descriptors, I loop through the corners of an image and create 40x40 patches. I then resize it to 8x8 and normalize it. I finally return a list of all these descriptors. I do so for each image.

3. Matching these feature descriptors between two images :

In order to match the feature descriptors, I calculate the distance between each pair of descriptors and if the fraction of the lowest two errors is smaller than 0.6 then I add this pair to my list of matchings.

4. Use a robust method (RANSAC) to compute a homography:

After implementing the RANSAC algorithm, I got this homography matrix H: