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Algorithm for Projective Reconstruction with Occlusions |
LIU ShiGang1,2, WU ChengKe1, LI LiangFu2, PENG YaLi1 |
1.National Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071 2.School of Computer Science, Shanxi Normal University, Xi’an 710065 |
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Abstract An algorithm for projective reconstruction with occlusions is presented. In this algorithm the reprojective points replace all the occlusion points, thus projective reconstruction is obtained. After several iterations, the positions of the occlusion are found and the accurate projective reconstruction could be finished. The innovation of the algorithm is that images and image points are treated uniformly. The experimental results of both simulated data and realworld data show that the algorithm is efficient and robust and it has a good property of convergence with small reprojection errors.
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Received: 21 March 2005
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[1] Faugeras O. What Can be Seen in Three Dimensions with an Uncalibrated Stereo Rig? // Proc of the European Conference on Computer Vision. Ligure, Italy, 1992: 563578 [2] Baker P, Aloimonos Y. Structure from Motion of Parallel Lines // Proc of the European Conference on Computer Vision. Prague, Czechoslovakia, 2004: 229240 [3] Liu Y, Wu C K, Tsui H. A Practical Approach for 3D Building Modeling from Uncalibrated Video Sequences. International Journal of Image and Graphics, 2002, 2(2): 287307 [4] Pollefeys M, Verbiest F, Gool L. Surviving Dominant Planes in Uncalibrated Structure and Motion Recovery // Proc of the European Conference on Computer Vision. Copenhagen, Denmark, 2002: 837851 [5] Quan L, Lhuillier M. Structure from Motion from Three Affine Views // Proc of the International Conference on Pattern Recognition. Quebec, Canada, 2002, Ⅳ: 16 [6] Ke Q, Kanade T. Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. San Diego, USA, 2005: 739746 [7] Vidal R, Ma Y, Soatto S, et al. TwoView Multibody Structure from Motion. International Journal of Computer Vision, 2006, 68(1): 725 [8] Liu Shigang, Wu Chengke, Tang Li, et al. A Robust SelfCalibration Method Based on Weighted Iteration. Journal of Electronics, 2006, 23(5): 713717 [9] Sturm P. MultiView Geometry for General Camera Models // Proc of the IEEE Conference on Computer Vision and Pattern Recognition. San Diego, USA, 2005: 206212 [10] Tomasi C, Kanade T. Shape and Motion from Image Streams under Orthography: A Factorization Method. International Journal of Computer Vision, 1992, 9(2): 137154 [11] Sturm P, Triggs B. A Factorization Based Algorithm for MultiImage Projective Structure and Motion // Proc of the European Conference on Computer Vision. Cambridge, UK, 1996: 709720 [12] Heyden A, Berthilsson R, Sparr G. An Iterative Factorization Method for Projective Structure and Motion from Image Sequences. Image and Vision Computing, 1999, 17(13): 981991 [13] Jacobs D W. Linear Fitting with Missing Data: Applications to StructurefromMotion and to Characterizing Intensity Images // Proc of the Conference on Computer Vision and Pattern Recognition. San Jun, Puerto Rico, 1997: 206212 [14] Martinec D, Pajdla T. Outlier Detection for FactorizationBased Reconstruction from Perspective Images with Occlusions // Proc of the Conference on Photogrammetric Computer Vision. Graz, Austria, 2002: 161164 [15] Heyden A. Projective Structure and Motion from Image Sequences Using Subspace Methods // Proc of the 10th Scandinavian Conference on Image Analysis. Lappenraanta, Finland, 1997: 963968 [16] Liu Shigang, Wu Chengke, Tang Li, et al. An Iterative Factorization Method Based on Rank 1 for Projective Structure and Motion. IEICE Trans on Information and Systems, 2005, 88(9): 21832188 [17] Liu Shigang, Wu Chengke, Tang Li, et al. A New SelfCalibration Algorithm Based on Linear Iteration. Acta Electronica Sinica, 2004, 32(10): 17161719 (in Chinese) (刘侍刚,吴成柯,唐 丽,等.一种基于线性迭代自定标方法.电子学报, 2004, 32(10): 17161719) |
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