A review of today's multi-view reconstruction

被引：0
|
作者：
Luo S. [1 ,2 ]
Gong Z. [2 ]
Ma G. [1 ]
机构：
[1] College of Mechanical and Electrical Engineering, Wenzhou University
[2] School of Mechatronics Engineering and Automation, Shanghai University
来源：
Jiqiren/Robot | 2010年 / 32卷 / 05期
关键词：
Cue for reconstruction; Integration of multiple reconstruction cues; Integration of multiple reconstruction methods; Multi-view reconstruction; Reconstruction accuracy; Reconstruction algorithm;
D O I：
10.3724/SP.J.1218.2010.00695
中图分类号：
学科分类号：
摘要：
This paper reviews today's algorithms about multi-view reconstruction. Firstly, the classification and evaluation methods for multi-view reconstruction are introduced. Secondly, some constraints, such as photo-consistency and visibility, are analyzed. Then, some typical algorithms are discussed, such as depth map, space carving, deformable model, objective function optimization (including the level set method, graph cuts method), seed-growing method, and probability estimation method (including Markov-field method, EM method). Some shortcomings in all of these algorithms are discussed. A new 3D reconstruction idea integrating some of aforementioned reconstruction methods and reconstruction cues is proposed to improve the integrity and accuracy of multi-view reconstruction.
引用
收藏
页码：695 / 704
页数：9
相关论文
共 102 条
  • [1] Broadhurst A., A probabilistic framework for space carving, (2001)
  • [2] Kutulakos K.N., Seitz S.M., A theory of shape by space carving, International Journal of Computer Vision, 38, 3, pp. 199-218, (2000)
  • [3] Yang R., Pollefeys M., Welch G., Dealing with textureless regions and specular highlights: A progressive space carving scheme using a novel photo-consistency measure, IEEE International Conference on Computer Vision, pp. 576-584, (2003)
  • [4] Osher S.J., Fedkiw R.P., Level Set Methods and Dynamic Implicit Surfaces, (2002)
  • [5] Enright D., Losasso F., Fedkiw R., A fast and accurate semi-Lagrangian particle level set method, Computers and Structures, 83, 6-7, pp. 479-490, (2005)
  • [6] Faugeras O., Keriven R., Complete dense stereovision using level set methods, European Conference on Computer Vision, pp. 379-393, (1998)
  • [7] Sung J., Kanade T., Kim D., A unified gradient-based approach for combining ASM into AAM, International Journal of Computer Vision, 75, 2, pp. 297-309, (2007)
  • [8] Solem J.E., Overgaard N.C., A Geometric Formulation of Gradient Descent for Variational Problems with Moving Surfaces, 3459, pp. 419-430, (2005)
  • [9] Solem J.E., Overgaard N.C., A Gradient Descent Procedure for Variational Dynamic Surface Problems with Constraints, 3752, pp. 332-343, (2005)
  • [10] Memisevic R., Hinton G., Improving dimensionality reduction with spectral gradient descent, Neural Networks, 18, 5-6, pp. 702-710, (2005)
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