3D Model Retrieval based on Normal Vector Interpolation Method
In this paper, we proposed the distribution of mesh
normal vector direction as a feature descriptor of a 3D model. A
normal vector shows the entire shape of a model well. The
distribution of normal vectors was sampled in proportion to each
polygon's area so that the information on the surface with less surface
area may be less reflected on composing a feature descriptor in order
to enhance retrieval performance. At the analysis result of ANMRR,
the enhancement of approx. 12.4%~34.7% compared to the existing
method has also been indicated.
[1] Ryutarou Ohbuchi, Takahiro Minamitani, Tsuyoshi Takei,
"Shape-Simility Search of 3D Models by using Enhanced Shape
Functions", IJCAT, Vol. 23, No. 2/3/4 pp.70-85, 2005.
[2] Eric Lengyel, Mathmetics for 3D Game Programming and Computer
Graphics Second Edition, 2004.
[3] YS Joo, Comparison of Polyhedra and Level Sets as Geometry
Reconstruction Models, Segang University, 2003.
[4] Benjamin Bustos, "Feature-Based Similarity Search in 3D Object
Databases", ACM Computing Surveys, Vol. 37, No. 4, pp.345-387, 2005.
[5] Ding-Yun Chen, Xiao-Pei Tian, Yu-Te Shen, Ming Ouhyoung, "On
Visual Similarity Based 3D Model Retrieval", Proceedings of
EUROGRAPHICS, Vol. 22, 2003.
[6] Robert Osada, Thomas Funkhouser, Bernard Chazelle and David
Dobkin, "Shape Distributions," Transactions on ACM Graphics, Vol.
21, pp.807-832, 2002.
[7] Philip Shilane, Michael Kazhdan, Patrick Min and Thomas Funkhouser,
"The Princeton Shape Benchmark", Proceedings of the Shape Modeling
International, pp. 388-399, 2004.
[8] M Lu, H Luo, J S Pan, "3D Model Retrieval Based on Vector
Quantisation Index Histograms", Journal of Physics, pp.437-41, 2006.
[9] US Ju, Computer Graphics learning by OpenGL, 2006.
[10] T. Zaharia and F. Preteux, "Results of 3D Shape Core Experiment,"
ISO/IEC JTC1/SC29/WG11 M6315, 2000.
[11] T. Zaharia and F. Preteux, "3D Shape Core Experiment: Semantic
Versus Geometric Categorization of 3D Mesh Models," ISO/IEC
JTC1/SC29/WG11 M6104, 2000.
[12] T. Zaharia and F. Prêeux, "3D Shape-based Retrieval within The
MPEG-7 Framework", Proc. SPIE Conf. on Nonlinear Image.
Processing and Pattern Analysis XII, vol.4304, pp.133-145, 2001.
[1] Ryutarou Ohbuchi, Takahiro Minamitani, Tsuyoshi Takei,
"Shape-Simility Search of 3D Models by using Enhanced Shape
Functions", IJCAT, Vol. 23, No. 2/3/4 pp.70-85, 2005.
[2] Eric Lengyel, Mathmetics for 3D Game Programming and Computer
Graphics Second Edition, 2004.
[3] YS Joo, Comparison of Polyhedra and Level Sets as Geometry
Reconstruction Models, Segang University, 2003.
[4] Benjamin Bustos, "Feature-Based Similarity Search in 3D Object
Databases", ACM Computing Surveys, Vol. 37, No. 4, pp.345-387, 2005.
[5] Ding-Yun Chen, Xiao-Pei Tian, Yu-Te Shen, Ming Ouhyoung, "On
Visual Similarity Based 3D Model Retrieval", Proceedings of
EUROGRAPHICS, Vol. 22, 2003.
[6] Robert Osada, Thomas Funkhouser, Bernard Chazelle and David
Dobkin, "Shape Distributions," Transactions on ACM Graphics, Vol.
21, pp.807-832, 2002.
[7] Philip Shilane, Michael Kazhdan, Patrick Min and Thomas Funkhouser,
"The Princeton Shape Benchmark", Proceedings of the Shape Modeling
International, pp. 388-399, 2004.
[8] M Lu, H Luo, J S Pan, "3D Model Retrieval Based on Vector
Quantisation Index Histograms", Journal of Physics, pp.437-41, 2006.
[9] US Ju, Computer Graphics learning by OpenGL, 2006.
[10] T. Zaharia and F. Preteux, "Results of 3D Shape Core Experiment,"
ISO/IEC JTC1/SC29/WG11 M6315, 2000.
[11] T. Zaharia and F. Preteux, "3D Shape Core Experiment: Semantic
Versus Geometric Categorization of 3D Mesh Models," ISO/IEC
JTC1/SC29/WG11 M6104, 2000.
[12] T. Zaharia and F. Prêeux, "3D Shape-based Retrieval within The
MPEG-7 Framework", Proc. SPIE Conf. on Nonlinear Image.
Processing and Pattern Analysis XII, vol.4304, pp.133-145, 2001.
@article{"International Journal of Engineering, Mathematical and Physical Sciences:54439", author = "Ami Kim and Oubong Gwun and Juwhan Song", title = "3D Model Retrieval based on Normal Vector Interpolation Method", abstract = "In this paper, we proposed the distribution of mesh
normal vector direction as a feature descriptor of a 3D model. A
normal vector shows the entire shape of a model well. The
distribution of normal vectors was sampled in proportion to each
polygon's area so that the information on the surface with less surface
area may be less reflected on composing a feature descriptor in order
to enhance retrieval performance. At the analysis result of ANMRR,
the enhancement of approx. 12.4%~34.7% compared to the existing
method has also been indicated.", keywords = "Interpolated Normal Vector, Feature Descriptor, 3DModel Retrieval.", volume = "3", number = "9", pages = "636-4", }