Data driven composite shape descriptor design for shape
retrieval with a VoR-Tree
We develop a data driven method (probability model) to construct a composite
shape descriptor by combining a pair of scale-based shape descriptors. The selection of a pair
of scale-based shape descriptors is modeled as the computation of the union of two events, i.e.,
retrieving similar shapes by using a single scale-based shape descriptor. The pair of scale-based
shape descriptors with the highest probability forms the composite shape descriptor. Given a
shape database, the composite shape descriptors for the shapes constitute a planar point set.
A VoR-Tree of the planar point set is then used as an indexing structure for efficient query
operation. Experiments and comparisons show the effectiveness and efficiency of the proposed
composite shape descriptor.
关键词:
shape descriptor,
shape retrieval,
shape analysis,
data-driven model