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Shape Matching and Object Recognition Using Shape Contexts (2001)

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by Serge Belongie , Jitendra Malik , Jan Puzicha
Venue:IEEE Transactions on Pattern Analysis and Machine Intelligence
Citations:1804 - 21 self
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BibTeX

@ARTICLE{Belongie01shapematching,
    author = {Serge Belongie and Jitendra Malik and Jan Puzicha},
    title = {Shape Matching and Object Recognition Using Shape Contexts},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    year = {2001},
    volume = {24},
    pages = {509--522}
}

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Abstract

We present a novel approach to measuring similarity between shapes and exploit it for object recognition. In our framework, the measurement of similarity is preceded by (1) solv- ing for correspondences between points on the two shapes, (2) using the correspondences to estimate an aligning transform. In order to solve the correspondence problem, we attach a descriptor, the shape context, to each point. The shape context at a reference point captures the distribution of the remaining points relative to it, thus offering a globally discriminative characterization. Corresponding points on two similar shapes will have similar shape con- texts, enabling us to solve for correspondences as an optimal assignment problem. Given the point correspondences, we estimate the transformation that best aligns the two shapes; reg- ularized thin plate splines provide a flexible class of transformation maps for this purpose. The dissimilarity between the two shapes is computed as a sum of matching errors between corresponding points, together with a term measuring the magnitude of the aligning trans- form. We treat recognition in a nearest-neighbor classification framework as the problem of finding the stored prototype shape that is maximally similar to that in the image. Results are presented for silhouettes, trademarks, handwritten digits and the COIL dataset.

Keyphrases

object recognition using shape context    shape matching    shape context    correspondence problem    object recognition    transformation map    point correspondence    ularized thin plate spline    similar shape con text    coil dataset    flexible class    discriminative characterization    stored prototype shape    novel approach    similar shape    reference point    optimal assignment problem    nearest-neighbor classification framework   

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