Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Harmonic Shape Histograms for 3D Shape Classification and Retrieval J. Fehr, H. Burkhardt
 

Summary: Harmonic Shape Histograms for 3D Shape Classification and Retrieval
J. Fehr, H. Burkhardt
Chair of Pattern Recognition and Image Processing
Albert-Ludwig-University
Freiburg, Germany
Abstract
In this paper, we present a novel approach towards 3D
shape recognition and retrieval using histograms of rota-
tion invariant local features. Features are extracted for ev-
ery point of voxelized 3D shape objects by use of functions
on spheres which are invariant towards rotation of the ob-
ject. The fast computation of the local features is performed
via convolution methods in frequency space. Histograms of
these features describe an object in terms of distributions
of local geometric properties such as orientation and an-
gle of edges, distances and convexity. Object classification
is performed by Support Vector Machines with histogram-
intersection kernels. In experiments on the Princeton Shape
Benchmark [1], our approach outperformed many existing
methods in several classification and retrieval tasks.

  

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

 

Collections: Computer Technologies and Information Sciences