tailieunhanh - Image alignment

Invite you to consult the lecture content "Image alignment" below. Contents of lectures introduce to you the content: A look into the past, bing streetside images, image alignment, alignment as fitting, fitting an affine transformation. Hopefully document content to meet the needs of learning, work effectively. | Image alignment A look into the past A look into the past Leningrad during the blockade Bing streetside images Image alignment: Applications Panorama stitching Recognition of object instances Image alignment: Challenges Small degree of overlap Occlusion, clutter Intensity changes Image alignment Two broad approaches: Direct (pixel-based) alignment Search for alignment where most pixels agree Feature-based alignment Search for alignment where extracted features agree Can be verified using pixel-based alignment Alignment as fitting Previous lectures: fitting a model to features in one image Find model M that minimizes M xi Alignment as fitting Previous lectures: fitting a model to features in one image Alignment: fitting a model to a transformation between pairs of features (matches) in two images Find model M that minimizes Find transformation T that minimizes M xi T xi xi ' 2D transformation models Similarity (translation, scale, rotation) Affine Projective (homography) Let’s start with affine transformations Simple fitting procedure (linear least squares) Approximates viewpoint changes for roughly planar objects and roughly orthographic cameras Can be used to initialize fitting for more complex models Fitting an affine transformation Assume we know the correspondences, how do we get the transformation? Fitting an affine transformation Linear system with six unknowns Each match gives us two linearly independent equations: need at least three to solve for the transformation parameters Feature-based alignment outline Feature-based alignment outline Extract features Feature-based alignment outline Extract features Compute putative matches Feature-based alignment outline . | Image alignment A look into the past A look into the past Leningrad during the blockade Bing streetside images Image alignment: Applications Panorama stitching Recognition of object instances Image alignment: Challenges Small degree of overlap Occlusion, clutter Intensity changes Image alignment Two broad approaches: Direct (pixel-based) alignment Search for alignment where most pixels agree Feature-based alignment Search for alignment where extracted features agree Can be verified using pixel-based alignment Alignment as fitting Previous lectures: fitting a model to features in one image Find model M that minimizes M xi Alignment as fitting Previous lectures: fitting a model to features in one image Alignment: fitting a model to a