Methods based on distinguished regions (transformation covariant detectable regions) have achieved considerable success in object recognition, retrieval and matching problems in both still images and videos. The chapter focuses on a method exploiting local coordinate systems (local affine frames) established on maximally stable extremal regions. We provide a taxonomy of affine-covariant constructions of local coordinate systems, prove their affine covariance and present algorithmic details on their computation. Exploiting processes proposed for computation of affine-invariant local frames of reference, tentative region-to-region correspondences are established. Object recognition is formulated as a problem of finding a maximal set of geometrically consistent matches. State of the art results are reported on standard, publicly available, object recognition tests (COIL-100, ZuBuD, FOCUS). Change of scale, illumination conditions, out-of-plane rotation, occlusion , locally anisotropic scale change and 3D translation of the viewpoint are all present in the test problems.
CITATION STYLE
Obdržálek, Š., & Matas, J. (2006). Object Recognition Using Local Affine Frames on Maximally Stable Extremal Regions (pp. 83–104). https://doi.org/10.1007/11957959_5
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