We address the problem of contour-based perceptual grouping using a user-defined vocabulary of simple part models. We train a family of classifiers on the vocabulary, and apply them to a region oversegmentation of the input image to detect closed contours that are consistent with some shape in the vocabulary. Given such a set of consistent cycles, they are both abstracted and categorized through a novel application of an active shape model also trained on the vocabulary. From an image of a real object, our framework recovers the projections of the abstract surfaces that comprise an idealized model of the object. We evaluate our framework on a newly constructed dataset annotated with a set of ground truth abstract surfaces. © 2010 Springer-Verlag.
CITATION STYLE
Sala, P., & Dickinson, S. (2010). Contour grouping and abstraction using simple part models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6315 LNCS, pp. 603–616). Springer Verlag. https://doi.org/10.1007/978-3-642-15555-0_44
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