Covering the Space of Tilts: Application to affine invariant image comparison

Abstract : We propose a mathematical method to analyze the numerous algorithms performing Image Matching by Affine Simulation (IMAS). To become affine invariant they apply a discrete set of affine transforms to the images, previous to the comparison of all images by a Scale Invariant Image Matching (SIIM), like SIFT. Obviously this multiplication of images to be compared increases the image matching complexity. Three questions arise: a) what is the best set of affine transforms to apply to each image to gain full practical affine invariance? b) what is the lowest attainable complexity for the resulting method? c) how to choose the underlying SIIM method? We provide an explicit answer and a mathematical proof of quasi-optimality of the solution to the first question. As an answer to b) we find that the near-optimal complexity ratio between full affine matching and scale invariant matching is more than halved, compared to the current IMAS methods. This means that the number of key points necessary for affine matching can be halved, and that the matching complexity is divided by four for exactly the same performance. This also means that an affine invariant set of descriptors can be associated with any image. The price to pay for full affine invariance is that the cardinality of this set is 6.34 times larger than for a SIIM.
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SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2018
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https://hal.archives-ouvertes.fr/hal-01589522
Contributeur : Mariano Rodríguez Guerra <>
Soumis le : lundi 19 février 2018 - 14:19:39
Dernière modification le : dimanche 29 avril 2018 - 01:11:59

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  • HAL Id : hal-01589522, version 2

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Mariano Rodríguez, Julie Delon, Jean-Michel Morel. Covering the Space of Tilts: Application to affine invariant image comparison. SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2018. 〈hal-01589522v2〉

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