TY - GEN
T1 - A 3D shape retrieval method based on continuous spherical wavelet transform
AU - Liu, Zhenbao
AU - Mitani, Jun
AU - Fukui, Yukio
AU - Nishihara, Seiichi
PY - 2007
Y1 - 2007
N2 - Recently, many efforts have concentrated on finding efficient content based retrieval methods of 3D objects. In this paper, we proposed a new retrieval method. The method is constructed on a shape descriptor based on continuous spherical wavelet transform. Continuous 2D wavelet transform has extinct advantages in content based image retrieval. The continuous wavelet transform can be extended from two dimensions to more dimensions, for example, spherical space, with the same properties. As a natural extension, continuous spherical wavelet transform can realize a spherical analysis. Therefore, we map a shape into a unit sphere by spherical parameterization, followed by continuous spherical wavelet transform of the spherical function. This method is our contribution. The result of the transform can be as a new descriptor and be used to match the dissimilarity of two shapes. We have examined our method on a small database of general objects and it is confirmed to be efficient.
AB - Recently, many efforts have concentrated on finding efficient content based retrieval methods of 3D objects. In this paper, we proposed a new retrieval method. The method is constructed on a shape descriptor based on continuous spherical wavelet transform. Continuous 2D wavelet transform has extinct advantages in content based image retrieval. The continuous wavelet transform can be extended from two dimensions to more dimensions, for example, spherical space, with the same properties. As a natural extension, continuous spherical wavelet transform can realize a spherical analysis. Therefore, we map a shape into a unit sphere by spherical parameterization, followed by continuous spherical wavelet transform of the spherical function. This method is our contribution. The result of the transform can be as a new descriptor and be used to match the dissimilarity of two shapes. We have examined our method on a small database of general objects and it is confirmed to be efficient.
KW - 3D object
KW - Content based retrieval
KW - Continuous spherical wavelet transform
KW - Shape descriptor
UR - http://www.scopus.com/inward/record.url?scp=54949130196&partnerID=8YFLogxK
M3 - 会议稿件
AN - SCOPUS:54949130196
SN - 9780889866447
T3 - Proceedings of the 9th IASTED International Conference on Computer Graphics and Imaging, CGIM 2007
SP - 21
EP - 26
BT - Proceedings of the 9th IASTED International Conference on Computer Graphics and Imaging, CGIM 2007
T2 - 9th IASTED International Conference on Computer Graphics and Imaging, CGIM 2007
Y2 - 13 February 2007 through 15 February 2007
ER -