Traditional approach and deep learning approach to estimate homography between 2 sets of images. Implemented supervised and unsupervised deep learning to estimate homography
- We encode each feature point for matching. To obtain encodings, we take a patch of size 41x41 around the feature point, then apply gaussian blur and sub-sample a 8x8 patch from it. This patch is then flattened to a feature vector of size 64x1 and standardized to set mean=0 and variance=1
- Image Stitching using traditional approach
- Homography estimation by deep learning approach
- MCE - Mean Corner Error
