Object Recognition as Many-to-Many Feature Matching
نویسندگان
چکیده
منابع مشابه
Many-to-Many Feature Matching in Object Recognition
One of the bottlenecks of current recognition (and graph matching) systems is their assumption of one-to-one feature (node) correspondence. This assumption breaks down in the generic object recognition task where, for example, a collection of features at one scale (in one image) may correspond to a single feature at a coarser scale (in the second image). Generic object recognition therefore req...
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The mainstream object categorisation community relies heavily on object representations consisting of local image features, due to their ease of recovery and their attractive invariance properties. Object categorisation is therefore formulated as finding, that is, ‘detecting’, a one-to-one correspondence between image and model features. This assumption breaks down for categories in which two e...
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Please cite this article in press as: M.F. Demirci e doi:10.1016/j.cviu.2010.12.012 Matching configurations of image features, represented as attributed graphs, to configurations of model features is an important component in many object recognition algorithms. Noisy segmentation of images and imprecise feature detection may lead to graphs that represent visually similar configurations that do ...
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Object recognition systems have their roots in the AI community, and originally addressed the problem of object categorization. These early systems, however, were limited by their inability to bridge the representational gap between low-level image features and high-level object models, hindered by the assumption of one-to-one correspondence between image and model features. Over the next thirt...
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ژورنال
عنوان ژورنال: International Journal of Computer Vision
سال: 2006
ISSN: 0920-5691,1573-1405
DOI: 10.1007/s11263-006-6993-y