Lior Shapira, Shy Shalom, Ariel Shamir, Daniel Cohen-Or, and Richard Hao Zhang
In this paper we address the problem of finding analogies between parts of 3D
objects. By partitioning an object into meaningful parts and finding analogous
parts in other objects, not necessarily of the same type, many analysis and
modeling tasks could be enhanced. For instance, partial match queries can be
formulated, annotation of parts in objects can be utilized, and
modeling-by-parts applications could be supported. We define a similarity
measure between two parts based not only on their local signatures and
geometry, but also on their context within the shape to which they belong.
In our approach, all objects are hierarchically segmented (e.g. using the shape
diameter function), and each part is given a local signature. However, to find
corresponding parts in other objects we use a context enhanced part-in-whole
matching. Our matching function is based on bi-partite graph matching and is
computed using a flow algorithm which takes into account both local geometrical
features and the partitioning hierarchy. We present results on finding part
analogies among numerous objects from shape repositories, and demonstrate
sub-part queries using an implementation of a simple search and retrieval
application. We also demonstrate a simple annotation tool that carries textual
tags of object parts from one model to many others using analogies, laying a
basis for semantic text based search.
In International Journal of Computer Vision
Publisher Springer-Verlag New York, Inc.
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