IEEE Trans Image Process - Robust pairwise matching of interest points with complex wavelets.

Tópicos

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Resumo

We present a matching framework to find robust correspondences between image features by considering the spatial information between them. To achieve this, we define spatial constraints on the relative orientation and change in scale between pairs of features. A pairwise similarity score which measures the similarity of features based on these spatial constraints is considered. The pairwise similarity scores for all pairs of candidate correspondences are then accumulated in a 2D similarity space. Robust correspondences can be found by searching for clusters in the similarity space, since actual correspondences are expected to form clusters that satisfy similar spatial constraints in this space. As it is difficult to achieve reliable and consistent estimates of scale and orientation, an additional contribution is that these parameters do not need to be determined at the interest point detection stage, which differs from conventional methods. Polar matching of dual-tree complex wavelet transform features is used, since it fits naturally into the framework with the defined spatial constraints. Our tests show that the proposed framework is capable of producing robust correspondences with higher correspondence ratios and reasonable computational efficiency, compared to other well-known algorithms.

Resumo Limpo

present match framework find robust correspond imag featur consid spatial inform achiev defin spatial constraint relat orient chang scale pair featur pairwis similar score measur similar featur base spatial constraint consid pairwis similar score pair candid correspond accumul d similar space robust correspond can found search cluster similar space sinc actual correspond expect form cluster satisfi similar spatial constraint space difficult achiev reliabl consist estim scale orient addit contribut paramet need determin interest point detect stage differ convent method polar match dualtre complex wavelet transform featur use sinc fit natur framework defin spatial constraint test show propos framework capabl produc robust correspond higher correspond ratio reason comput effici compar wellknown algorithm

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