Abstract
The problem of object recognition can be formulated as matching feature sets of different objects. Segmentation errors and scale difference result in many-to-many matching of feature sets, rather than one-to-one. This paper extends a previous algorithm on many-to-many graph matching. The proposed work represents graphs, which correspond to objects, isometrically in the geometric space under the l 1 norm. Empirical evaluation of the algorithm on a set of recognition trails, including a comparison with the previous approach, demonstrates the efficacy of the overall framework.
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Demirci, M.F., Osmanlıoğlu, Y. (2009). Many-to-Many Matching under the l 1 Norm. In: Foggia, P., Sansone, C., Vento, M. (eds) Image Analysis and Processing – ICIAP 2009. ICIAP 2009. Lecture Notes in Computer Science, vol 5716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04146-4_84
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DOI: https://doi.org/10.1007/978-3-642-04146-4_84
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