一种基于面片的三维重建算法

doi:10.3969/j.issn.1000-3428.2012.14.060

计算机工程 ›› 2012, Vol. 38 ›› Issue (14): 199-202. doi: 10.3969/j.issn.1000-3428.2012.14.060

一种基于面片的三维重建算法

岳立廷，于明，于洋，阎刚，薛翠红

(河北工业大学计算机科学与软件学院，天津 300401)

收稿日期:2011-09-02 出版日期:2012-07-20 发布日期:2012-07-20
作者简介:岳立廷(1985－)，男，硕士研究生，主研方向：图像处理，模式识别；于明，教授；于洋，博士研究生；阎刚、薛翠红，讲师
基金资助:
河北省教育厅基金资助重点项目(ZD200911)

3D Reconstruction Algorithm Based on Facet

YUE Li-ting, YU Ming, YU Yang, YAN Gang, XUE Cui-hong

(School of Computer Science and Software, Hebei University of Technology, Tianjin 300401, China)

Received:2011-09-02 Online:2012-07-20 Published:2012-07-20

摘要/Abstract

摘要： 传统基于面片的多视角立体视觉算法在扩展面片时缺少空间几何约束，导致Poisson表面重建时生成错误顶点。为此，提出一种基于面片的三维重建算法。利用相邻面片初始化扩展面片，根据顶点k近邻的距离检测并去除离群顶点，从而得到物体表面的三维模型。实验结果证明了该算法的有效性和准确性。

关键词: 三维重建, 多视角, 空间几何约束, Poisson表面重建, k近邻, 离群点检测

Abstract: The PMVS algorithm does not add space geometric constraint during expanding spare points to dense points, and the Poisson surface reconstruction algorithm outputs a closed mesh model which contains wrong vertices. In order to solve this problem, this paper considers patches around the expanding one at the same time, detects the outlier vertices of triangle meshes according to k Nearest Neighbor(kNN) and removes extraneous portions of the mesh. Experimental result shows that the reconstruction algorithm is more smooth and more accurate.

Key words: 3D reconstruction, multiple views, space geometric constraint, Poisson surface reconstruction, k Nearest Neighbor(kNN), outlier detection

中图分类号:

TP911.73

岳立廷, 于明, 于洋, 阎刚, 薛翠红. 一种基于面片的三维重建算法[J]. 计算机工程, 2012, 38(14): 199-202.

YUE Li-Ting, XU Meng, XU Xiang, YAN Gang, XUE Cui-Gong. 3D Reconstruction Algorithm Based on Facet[J]. Computer Engineering, 2012, 38(14): 199-202.

http://www.ecice06.com/CN/Y2012/V38/I14/199

参考文献

[1] Paris S, Sillion F X, Quan Long. A Surface Reconstruction Method Using Global Graph Cut Optimization[J]. International Journal of Computer Vision, 2006, 66(2): 141-161.
[2] Pons J P, Keriven R, Faugeras O D. Multi-view Stereo Re- construction and Scene Flow Estimation with a Global Image Based Matching Score[J]. International Journal of Computer Vision, 2007, 72(2): 179-193.
[3] Tran S, Davis L S. 3D Surface Reconstruction Using Graph Cuts with Surface Constraints[C]//Proceedings of the 9th European Conference on Computer Vision. Graz, Austria: Springer, 2006: 219-231.
[4] Hornung A, Kobbelt L. Hierarchical Volumetric Multi-view Stereo Reconstruction of Manifold Surfaces Based on Dual Graph Embedding[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Washington D. C., USA: IEEE Computer Society, 2006: 503-510.
[5] Esteban C H, Schmitt F. Silhouette and Stereo Fusion for 3D Object Modeling[J]. Computer Vision and Image Understanding, 2004, 96(3): 367-392.
[6] Zaharescu A, Boyer E, Horaud R. Transformesh: A Topology Adaptive Mesh-based Approach to Surface Evolution[C]// Proceedings of the 8th Asia Conference on Computer Vision. Tokyo, Japan: Springer, 2007: 166-175.
[7] Furukawa Y, Ponce J. Carved Visual Hulls for Image-based Modeling[J]. International Journal of Computer Vision, 2009, 81(1): 53-67.
[8] Goesele M, Curless B, Seitz S. Multi-view Stereo Revisited[C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. New York, USA: IEEE Computer Society, 2006: 2402-2409.
[9] Strecha C, Fransens R, Gool V L. Combined Depth and Outlier Estimation in Multi-view Stereo[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Washington D. C., USA: IEEE Computer Society, 2006: 2394-2401.
[10] Bradley D, Boubekeur T, Heidrich W. Accurate Multi-view Reconstruction Using Robust Binocular Stereo and Surface Meshing[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Anchorage, USA: IEEE Press, 2008: 1-8.
[11] Lhuillier M, Quan Long. A Quasi-dense Approach to Surface Reconstruction from Uncalibrated Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(3): 418-433.
[12] Habbecke M, Kobbelt L. Iterative Multi-view Plane Fitting[C]// Proceedings of the 11th International Fall Workshop on Vision, Modeling, and Visualization. Aachen, Germany: Akademische Verlagsgesellschaft Aka GmbH, 2006: 73-80.
[13] Furukawa Y, Ponce J. Accurate, Dense, and Robust Multi-view Stereopsis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(8): 1362-1376.
[14] Kazhdan M, Bolitho M, Hoppe H. Poisson Surface Recon- struction[C]//Proceedings of the 4th Eurographics Symposium on Geometry Processing. Cagliari, Italy: Eurographics Association, 2006: 61-70.
[15] 张正友, 马颂德. 计算机视觉[M]. 北京: 科学出版社, 1998.
[16] Ramaswamy S, Rastogi R, Kyuseok S. Efficient Algorithms for Mining Outliers from Large Data Sets[C]//Proceedings of ACMSIGMOD International Conference on Management of Data. Dallas, USA: ACM Press, 2000: 427-438.
[17] 陆声链, 林士敏. 基于距离的孤立点检测研究[J]. 计算机工程与应用, 2004, 40(33): 73-75.

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