Multi-Level Recommendation for Sketch Based 3D Toy Modeling

Guang Yu Zhu; Jin Wang; Guo Dong Lu

doi:10.4028/www.scientific.net/AMR.472-475.145

Paper Titles

Effect of Passivation on Pitting Corrosion of 316L Stainless Steel in Concentrated Seawater
p.127

Milling Parameter Optimization Based on Control of Aluminum Alloy 7475 Surface Roughness
p.132

A Novel Electrodeposited Ni-Cr-Al Nanocomposite with Improved Oxidation Resistance
p.137

Comparison of Hot Corrosion Resistance of YSZ and CYSZ Thermal Barrier Coatings in Presence of Sulfate-Vanadate Molten Salts
p.141

Multi-Level Recommendation for Sketch Based 3D Toy Modeling
p.145

Effects on Corrosion Resistance of Ce-Sealed Ni-P Coatings with Ni-Low P and Ni-Medium P
p.151

Preparation and Photocatalytic Activity of Ag-TiO₂/CNT Photocatalyst
p.157

Correlation of Surface Alloyed Microstructure of Pure Magnesium With its Corrosion Behavior
p.161

Microstructure Characteristics of Fe-xCr-C Hardfacing Alloys
p.165

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 472-475Multi-Level Recommendation for Sketch Based 3D Toy...

Multi-Level Recommendation for Sketch Based 3D Toy Modeling

Abstract:

Models recommendation is always a key part in part-composition system based on sketch. In this paper, proper models are suggested via three steps. Firstly, the possible type of model parts is suggested according to the topological features. Then toy parts that have similar profile types with the inputted sketches are clustered and recommended by lineage clustering method. Finally, based on the promoted $1 recognizer, the suggested parts are sorted according to the shape similarity with the inputted sketch. Experimental results show that the models can be recommended quickly and properly via our method.

You might also be interested in these eBooks

Advanced Manufacturing Technology, ICMSE 2012

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 472-475)

Pages:

145-150

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.472-475.145

Citation:

Cite this paper

Online since:

February 2012

Authors:

Guang Yu Zhu, Jin Wang, Guo Dong Lu

Keywords:

Lineage Clustering, Part-Composition System, Sketch Based Recommendation, Sketch-Based Modeling

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Y. Liu, C. Ma and D. Zhang: IEEE Computer Graphics & Applications Vol. 31(2) (2011), pp.49-57

Google Scholar

[2] A. Rivers, F. Durand and T. Igarashi: ACM Trans. Graph. Vol. 29(4) (2010), p.1

Google Scholar

[3] T. Funkhouser, et al.: ACM Trans. Graph. Vol. 23(3) (2004), p.652

Google Scholar

[4] J. Lee and T. Funkhouser, Sketch-based search and composition of 3d models. EUROGRAPHICS Workshop on Sketch-Based Interfaces and Modeling, (2008)

Google Scholar

[5] J. Pu, K. Lou and K. Ramani: Computer Aided Design & Applications Vol. 2(6) (2005), p.717

Google Scholar

[6] M. Eitz, K. Hildebrand, T. Boubekeur, and M. Alexa, Sketch-based 3D shape retrieval. ACM SIGGRAPH 2010 Talk Program, (2010)

DOI: 10.1145/1837026.1837033

Google Scholar

[7] Y. Liu, et al.: The Visual Computer Vol. 28 (2012)

Google Scholar

[8] Information on http://paulbourke.net/miscellaneous/dft/

Google Scholar

[9] J.O. Wobbrock, A.D. Wilson, and Y. Li, Gestures without Libraries, Toolkits or Training: A \$1 Recognizer for User Interface Prototypes. UIST'07, (2007), pp.159-168

DOI: 10.1145/1294211.1294238

Google Scholar

[10] Information on http://www.opencv.org.cn

Google Scholar