An Area Weighted Surface Sampling Method for 3D Model Retrieval

LI Haisheng; LIU Xuan; LAI Long; CAI Qiang; DU Junping

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(3): 484-488

LI Haisheng, LIU Xuan, LAI Long, et al., “An Area Weighted Surface Sampling Method for 3D Model Retrieval,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 484-488, 2014,

Citation:

LI Haisheng, LIU Xuan, LAI Long, et al., “An Area Weighted Surface Sampling Method for 3D Model Retrieval,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 484-488, 2014,

LI Haisheng, LIU Xuan, LAI Long, et al., “An Area Weighted Surface Sampling Method for 3D Model Retrieval,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 484-488, 2014,

Citation:

LI Haisheng, LIU Xuan, LAI Long, et al., “An Area Weighted Surface Sampling Method for 3D Model Retrieval,” Chinese Journal of Electronics, vol. 23, no. 3, pp. 484-488, 2014,

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An Area Weighted Surface Sampling Method for 3D Model Retrieval

1.
School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;
2.
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

Funds: This work is supported by National Basic Research Program of China (973 Program) (No. 2012CB821200), (No. 2012CB821206), Project Supported by National Natural Science Foundation of China (No. 61320106006), Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality (No. PHR201108075), Funding Project for Innovation on Science, Technology and Graduate Education in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality (No. PXM2013 014213 000030 00042300) and the Academic Innovation Foundation in Beijing Technology and Business University.

Received Date: 2012-09-01
Rev Recd Date: 2014-02-01
Publish Date: 2014-07-05

Abstract

Abstract

3D model feature extraction is a key step for geometric content based 3D model retrieval. A 3D model is usually expressed by patches and it has large amount of data. Pseudo-random sequential Monte Carlo surface sampling method is used to sample 3D model data. It has strong randomness. The sampling results are not uniform, which worsen the efficiency and precision of feature extraction. An area weighted surface sampling method for 3DModels is proposed. The larger area patches get the higher probability of sampling. The sampling points are evenly distributed in sampling space, which represent more accurate 3D model features. Experiments show that the proposed method needs less computing resources. Even when there are less sampling points, it can still keep high calculation accuracy and stability.
- 3D Model retrieval,
- Preprocessing,
- Feature extraction,
- Surface sampling,
- Area weighted

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References(14)

References

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