Transcription of Automatic Panoramic Image Stitching using Invariant …
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Automatic Panoramic Image Stitching using Invariant FeaturesMatthew Brown and David G. of Computer Science,University of British Columbia,Vancouver, paper concerns the problem of fully automatedpanoramic Image Stitching . Though the 1D problem (singleaxis of rotation) is well studied, 2D or multi-row Stitching ismore difficult. Previous approaches have used human inputor restrictions on the Image sequence in order to establishmatching images. In this work, we formulate Stitching as amulti- Image matching problem, and use Invariant local fea-tures to find matches between all of the images. Because ofthis our method is insensitive to the ordering, orientation,scale and illumination of the input images. It is also insen-sitive to noise images that are not part of a panorama, andcan recognise multiple panoramas in an unordered imagedataset.
The 4 parameter camera model is defined by K i = f i 0 0 0 f i 0 0 0 1 (2) and (using the exponential representation for rotations) R i = e[θ i] ×, [θ i] × = 0 −θ i3 θ i2 θ i3 0 −θ i1 −θ i2 θ i1 0 . (3) Ideally one would use image features that are invariant under this group of transformations. However, for small changes in ...
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