TY - JOUR
T1 - A new 3D shape retrieval method using spherical Healpix
AU - Liu, Zhenbao
AU - Mitani, Jun
AU - Fukui, Yukio
AU - Nishihara, Seiichi
N1 - Publisher Copyright:
© 2008 Information Processing Society of Japan.
PY - 2008
Y1 - 2008
N2 - Rapidly spreading 3D shape applications have led to the development of content-based 3D shape retrieval research. In this paper, we propose a new retrieval method using Spherical Healpix. Spherical Healpix is a new framework for efficient discretization and fast analysis or synthesis of functions defined on the sphere. We analyzed the construction process of this structure and defined a new Spherical Healpix Extent Function. We then analyzed this Spherical Healpix Extent Function using an inverse-construction process from the sphere to the Euclidean plane. We transformed the result of inverse-construction to the frequency domain using a 2D Fourier transform, instead of spherical harmonics, a well-known tool in spherical analysis. We obtained the low-frequency component in the frequency domain by using a Butterworth low-pass filter. The power spectrum of the low frequency component can be used as the feature vector to describe a 3D shape. This descriptor is extracted in the canonical coordinate frame; that is, each 3D-model is first normalized. We have examined this method on the Konstanz Shape Benchmark and SHREC data set, and confirmed its efficiency. We also compared this method with other methods on the same Konstanz Shape Benchmark and SHREC data set and evaluated the shape retrieval performanc.
AB - Rapidly spreading 3D shape applications have led to the development of content-based 3D shape retrieval research. In this paper, we propose a new retrieval method using Spherical Healpix. Spherical Healpix is a new framework for efficient discretization and fast analysis or synthesis of functions defined on the sphere. We analyzed the construction process of this structure and defined a new Spherical Healpix Extent Function. We then analyzed this Spherical Healpix Extent Function using an inverse-construction process from the sphere to the Euclidean plane. We transformed the result of inverse-construction to the frequency domain using a 2D Fourier transform, instead of spherical harmonics, a well-known tool in spherical analysis. We obtained the low-frequency component in the frequency domain by using a Butterworth low-pass filter. The power spectrum of the low frequency component can be used as the feature vector to describe a 3D shape. This descriptor is extracted in the canonical coordinate frame; that is, each 3D-model is first normalized. We have examined this method on the Konstanz Shape Benchmark and SHREC data set, and confirmed its efficiency. We also compared this method with other methods on the same Konstanz Shape Benchmark and SHREC data set and evaluated the shape retrieval performanc.
UR - http://www.scopus.com/inward/record.url?scp=77955800028&partnerID=8YFLogxK
U2 - 10.2197/ipsjjip.16.190
DO - 10.2197/ipsjjip.16.190
M3 - 文章
AN - SCOPUS:77955800028
SN - 0387-5806
VL - 16
SP - 190
EP - 200
JO - Journal of Information Processing
JF - Journal of Information Processing
ER -