Computer Science ›› 2015, Vol. 42 ›› Issue (6): 293-295.doi: 10.11896/j.issn.1002-137X.2015.06.061

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New Architecture for Extraction of 3D Model Features Based on Probabilistic Density Estimation of Local Surface Features

SUN Ting, ZHANG Jin-hua and GENG Guo-hua   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Feature extraction is a key issue for 3D model retrieval.A new architecture for extraction of 3D model features using probabilistic density estimation of local surface features was proposed.With the set of 3D local geometrical features,the local feature density of a chosen target point was evaluated using probabilistic density estimation methods.The 3D model can be described using the feature vector comprised of all local feature density values.The single-variate and multi-variate descriptors of 3D mesh model support the implementation of 3D model retrieval.The results show that the retrieval performance of the method is better than that of the statistical feature extraction methods.

Key words: Probabilistic density estimation,Feature fusion,Feature extraction

[1] 徐正光,陈宸.鲁棒且快速的特征点匹配算法[J].计算机科学,2013,40(2):294-296 Xu Zheng-guang,Chen Chen.Robust and Fast Feature Points Matching[J].Computer Science,2013,40(2):294-296
[2] 胡事民,杨永亮,来煜坤.数字几何处理研究进展[J].计算机学报,2009,2(8):1451-1469 Hu Shi-min,Yang Yong-liang,Lai Yu-kun.Research Progress of Digital Geometry Processing[J].Chinese Journal of Compu-ters,2009,2(8):1451-1469
[3] Castellani U,Cristani M,Murino V.Statistical 3D Shape Analysis by Local Generative Descriptors[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(12):2555-2560
[4] Horn B K P.Extended Gaussian images[J].Proceedings of the IEEE,1984,72(12):1671-1686
[5] Kang S,Ikeuchi K.The complex EGI:a new representation for 3-D pose determination[C]∥Proceedings of 5th International Central and Eastern European Conference on Multi-Agent Systems(CEEMAS 2007)Leipzig,Germany,2007,9:25-27
[6] Zaharia T,Preteux F.3D shape-based retrieval within theMPEG-7 framework [C]∥Proceedings of SPIE Conference on Nonlinear Image Processing and Patern Analysis XII.San Jose,2001:133-145
[7] Liu Zhen-bao,Bu Shu-hui,Kun Zhou,et al.A Survey on Partial Retrieval of 3D Shapes[J].Journal of Computer Science and Technology,2013,8(5):836-851
[8] 王刚,靳彦青,刘立柱,等.基于多特征融合的东亚文种识别[J].计算机科学,2013,0(1):260-263Wang Gang,Jin Yan-qing,Liu Li-zhu,et al.East Asian ScriptIdentification Based on Multi-feature[J].Computer Science,2013,0(1):260-263
[9] Akgül C B,Sankur B,Yemez Y,et al.Density based 3D shape descriptors[J].EURASIP Journal on Advances in Signal Processing,2007,2007:1-16
[10] Hardle W,Muller M,Sperlich S,et al.Nonparametric and Semiparametric Models[M].Springer Series in Statistics,Springer,Heidelberg,Germany,2004
[11] Scott D W.Multivariate Density Estimation:Theory,Practiceand Visualization[M].John Wiley & Sons,2008
[12] Comaniciu D,Ramesh V,Meer P.The variable bandwidth mean shift and data-driven scale selection[J].Proceedings of the 8th International Conference on Computer Vision(ICCV’01),Vancouver,BC,Canada,2001,7(1):438-445
[13] 黄云清.数值计算方法[M].北京:科学出版社,2010 Huang Yun-qing.Numerical Method[M].Beijing:Science Press,2010
[14] Sinha A,Gupta S.A Fast Nonparametric Noncausal MRF-Based Texture Synthesis Scheme Using a Novel FKDE Algorithm[J].IEEE Transactions on Image Processing,2010,19(3):561-572
[15] Shilane P,Min P,Kazhdan M,et al.The Princeton shape Benchmark[C]∥Proceedings of International Conference on Shape Modeling and Applications (SMI’04).Genova,Italy,2004:167-178
[16] Goodall S,Lewis P H,Martinez K,et al.SCULPTEUR:multimedia retrieval formuseums[C]∥ Image and Video Retrieval:Image and Video Retrieval (CIVR’04).Dublin,Ireland,2004:638-646
[17] 郭连朋,陈向宁,徐万朋,等.基于Kinect传感器的物体三维重建[J].四川兵工学报,2014,35(11):119-123 Guo Lian-peng,Chen Xiang-ning,Xu Wan-peng,et al.3D-object Reconstruction Based on kinect Sensor[J].Journal of Sichuan Ordnance,2014,5(11):119-123

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