Panorama stitching
For more details - Project Report
Repository - Github
Stitching multiple images with 30 − 50% overlap to generate a panorama using classical approach. Steps involve corner detection, ANMS, feature extraction and matching, RANSAC and estimating homography.
Input data
Undistorted images
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Corner detection
Harris corner & Adaptive Non-maximal Suppression (ANMS) for uniform distribution of features.
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Feature matching and RANSAC for outlier rejection
Match keypoints (encoded as feature vectors) across pair of images. Refine the matches using RANSAC.
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Stitch all images
Estimated homography using the refined matches, warp and stitch images with overlap.
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More panoramas
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