| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
Ji{\v r}{\' \i} Matas and {\v S}t{\v e}p{\' a}n Obdr{\v z}{\' a}lek
ABSTRACT
An approach to object recognition, based on matching of local image features, is presented. First, distinguished regions of data-dependent shape are robustly detected. On these regions, local affine frames are established using several affine invariant constructions. Direct comparison of photometrically normalised colour intensities in local, geometrically aligned frames results in a matching scheme that is invariant to piecewise-affine image deformations, but still remains very discriminative. Nevertheless, invariance to a wide range of local geometric and photometric transformations reduces the discriminative power – not all possible transformations are equiprobable. Probability of the transformations is estimated from matches established by the invariant method on the training data. The estimate is exploited in the recognition phase to favour local correspondences with more likely transformations. The potential of the approach is experimentally verified on COIL-100 – a publicly available image database. 99.9 recognition rate is obtained for 18 training views per object. |
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