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ICCV
2009
IEEE

Multiscale Symmetric Part Detection and Grouping

13 years 4 months ago
Multiscale Symmetric Part Detection and Grouping
Skeletonization algorithms typically decompose an object’s silhouette into a set of symmetric parts, offering a powerful representation for shape categorization. However, having access to an object’s silhouette assumes correct figure-ground segmentation, leading to a disconnect with the mainstream categorization community, which attempts to recognize objects from cluttered images. In this paper, we present a novel approach to recovering and grouping the symmetric parts of an object from a cluttered scene. We begin by using a multiresolution superpixel segmentation to generate medial point hypotheses, and use a learned affinity function to perceptually group nearby medial points likely to belong to the same medial branch. In the next stage, we learn higher granularity affinity functions to group the resulting medial branches likely to belong to the same object. The resulting framework yields a skeletal approximation that’s free of many of the instabilities plaguing...
Alex Levinshtein, Sven Dickinson, Cristian Sminchi
Added 13 Jul 2009
Updated 10 Jan 2010
Type Conference
Year 2009
Where ICCV
Authors Alex Levinshtein, Sven Dickinson, Cristian Sminchisescu
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