Take a sneak peek at the new NIST.gov and let us know what you think!
(Please note: some content may not be complete on the beta site.).

View the beta site
NIST logo

Publication Citation: 3D shape retrieval based on Multi-scale Integral Orientations

NIST Authors in Bold

Author(s): Afzal A. Godil; Stephane Bres; Asim Wagan;
Title: 3D shape retrieval based on Multi-scale Integral Orientations
Published: May 02, 2010
Abstract: In this paper we describe a novel 3D shape retrieval method based on Multi-scale Integral Orientations. In our approach, a 3D model after normalization is represented by a set of depth images captured uniformly on a unit circle. Then the shape descriptor based on the multiscale version of the localized gradient histogram is calculated for each depth image. Finally, the comparison is performed using a simple Euclidean distance to show the effectiveness of the shape descriptor for the 3D shape retrieval. We have then applied our algorithm on the Princeton shape benchmark and got results with performance similar to the Light Field Descriptor. In the future we are planning to use this descriptor with the bag of features and machine learning based approaches to get even better results.
Conference: Eurographics Workshop on 3D Object Retrieval (2010)
Pages: 4 pp.
Location: Norrköping, -1
Dates: May 2, 2010
Keywords: 3D shape retrieval, Multi-scale Integral Orientations, local features
Research Areas: Data Mining, Imaging
PDF version: PDF Document Click here to retrieve PDF version of paper (196KB)