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http://dx.doi.org/10.3745/KIPSTB.2010.17B.3.183

Realistic 3D Scene Reconstruction from an Image Sequence  

Jun, Hee-Sung (울산대학교 컴퓨터정보통신공학부)
Publication Information
The KIPS Transactions:PartB / v.17B, no.3, 2010 , pp. 183-188 More about this Journal
Abstract
A factorization-based 3D reconstruction system is realized to recover 3D scene from an image sequence. The image sequence is captured from uncalibrated perspective camera from several views. Many matched feature points over all images are obtained by feature tracking method. Then, these data are supplied to the 3D reconstruction module to obtain the projective reconstruction. Projective reconstruction is converted to Euclidean reconstruction by enforcing several metric constraints. After many triangular meshes are obtained, realistic reconstruction of 3D models are finished by texture mapping. The developed system is implemented in C++, and Qt library is used to implement the system user interface. OpenGL graphics library is used to realize the texture mapping routine and the model visualization program. Experimental results using synthetic and real image data are included to demonstrate the effectiveness of the developed system.
Keywords
Image-based Modeling; Projective Reconstruction; Euclidean Reconstruction; Structure From Motion; Texture Mapping;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Bruce D. Lucas and Takeo Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision," International Joint Conference on Artificial Intelligence, pp.674-679, 1981.
2 Jianbo Shi and Carlo Tomasi, "Good Features to Track," IEEE Conference on Computer Vision and Pattern Recognition, pp.593-600, 1994.   DOI
3 Qt Library (http://www.trolltech.com/)
4 (http://www.ces.clemson.edu/~stb/klt/) KLT : An Implementation of the Kanade-Lucas-Tomasi Feature Tracker
5 김성용, 한준희, "제약 조건을 이용한 셀프 캘리브레이션 방법," 정보과학회논문지:소프트웨어 및 응용 제28권 제4호 pp. 358-368, 2001년 4월   과학기술학회마을
6 D. Lowe, "Distinctive image features from scale-invariant key-points," International Journal of Computer Vision, 60(2), 91-110, 2004.   DOI
7 M. Woo, J. Neider, T. Davis, D. Shreiner, OpenGL Programming Guide, 3rd edition, Addison Wesley, 1999.
8 Q. Chen, "Multi-view Image-Based Rendering and Modeling," Ph. D. Dissertation, USC, 2000.
9 R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2000.
10 M. Han and T. Kanade, "Creating 3D Models with Uncalibrated Cameras," Proc. of IEEE Computer Society Workshop on the Application of Computer Vision, Dec. 2000.   DOI
11 Q. Chen and G. Medioni, "Efficient iterative solution to M-view projective reconstruction problem," Proc. IEEE CVPR 1999.   DOI
12 MOVI house data (http://www.inrialpes.fr/movi/pub/Images/ sequences/g3_vp_ra_s1/index.html)
13 W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C, Cambridge University Press, 1989.