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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 6/2014

01.08.2014 | Original Paper

Extrinsic calibration of heterogeneous cameras by line images

verfasst von: Dieu Sang Ly, Cédric Demonceaux, Pascal Vasseur, Claude Pégard

Erschienen in: Machine Vision and Applications | Ausgabe 6/2014

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Abstract

The extrinsic calibration refers to determining the relative pose of cameras. Most of the approaches for cameras with non-overlapping fields of view (FOV) are based on mirror reflection, object tracking or rigidity constraint of stereo systems whereas cameras with overlapping FOV can be calibrated using structure from motion solutions. We propose an extrinsic calibration method within structure from motion framework for cameras with overlapping FOV and its extension to cameras with partially non-overlapping FOV. Recently, omnidirectional vision has become a popular topic in computer vision as an omnidirectional camera can cover large FOV in one image. Combining the good resolution of perspective cameras and the wide observation angle of omnidirectional cameras has been an attractive trend in multi-camera system. For this reason, we present an approach which is applicable to heterogeneous types of vision sensors. Moreover, this method utilizes images of lines as these features possess several advantageous characteristics over point features, especially in urban environment. The calibration consists of a linear estimation of orientation and position of cameras and optionally bundle adjustment to refine the extrinsic parameters.
Vorheriger Artikel A traverse inspection system for high precision visual on-loom fabric defect detection
Nächster Artikel Graph-cut based interactive segmentation of 3D materials-science images

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Literatur
1.
Ansar, A., Daniilidis, K.: Linear pose estimation from points or lines. IEEE Trans. Pattern Anal. Mach. Intell. 25(5), 578–589 (2003)CrossRef
2.
Antone, M., Teller, S.: Scalable extrinsic calibration of omnidirectional image networks. Int. J. Comput. Vis. 49, 143–174 (2002)CrossRefMATH
3.
Barreto, J., Araujo, H.: Issues on the geometry of central catadioptric image formation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. II: 422–427 (2001)
4.
Barreto, J.P., Daniilidis, K.: Wide area multiple camera calibration and estimation of radial distortion. In: The fifth Workshop on Omnidirectional Vision, Camera Networks and Non-classical cameras (2004)
5.
Bartoli, A., Sturm, P.: Structure-from-motion using lines: representation, triangulation, and bundle adjustment. Comput. Vis. Image Underst. 100(3), 416–441 (2005)CrossRef
6.
Bastanlar, Y., Temizel, A., Yardimci, Y., Sturm, P.: Multi-view structure-from-motion for hybrid camera scenarios. Image Vis. Comput. 30(8), 557–572 (2012)CrossRef
7.
Bazin, J., Demonceaux, C., Vasseur, P., Kweon, I.: Motion estimation by decoupling rotation and translation in catadioptric vision. Comput. Vis. Image Underst. 114(2), 254–273 (2010)CrossRef
8.
Beardsley, P., Torr, P., Zisserman, A.: 3d model acquisition from extended image sequences. Proceedings of the Fourth European Conference on Computer Vision II, 683–695 (1996)
9.
Chang, P.: Omnidirectional structure from motion. In: IEEE Workshop on Omnidirectional Vision, pp. 127–133 (2000)
10.
Chen, X., Yang, J., Waibel, A.: Calibration of a hybrid camera network. In: International Conference on Computer Vision, pp. 150–155 (2003)
11.
Cruz Mota, J., Bogdanova, I., Paquier, B., Bierlaire, M., Thiran, J.: Scale invariant feature transform on the sphere: theory and applications. Int. J. Comput. Vis. 98(2), 217–241 (2012)CrossRefMATHMathSciNet
12.
Fischler, M., Bolles, R.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)CrossRefMathSciNet
13.
Fitzgibbon, A., Zisserman, A.: Automatic camera recovery for closed or open image sequences. In: European Conference on Computer Vision, pp. I: 311–326 (1998)
14.
Gasparini, S., Sturm, P.: Multi-view matching tensors from lines for general camera models. In: Computer Vision and Pattern Recognition Workshops, pp. 1–6 (2008)
15.
Geyer, C., Daniilidis, K.: A unifying theory for central panoramic systems and practical implications. In: European Conference on Computer Vision, pp. II: 445–461 (2000)
16.
Gluckman, J., Nayar, S.K.: Ego-motion and omnidirectional cameras. In: Proceedings of the Sixth International Conference on Computer Vision, pp. 999–2005 (1998)
17.
Hartley, R.: Euclidean reconstruction from uncalibrated views. In: Applications of Invariance in Computer Vision, pp. 237–256 (1993)
18.
Hartley, R.: In defense of the eight-point algorithm. IEEE Trans. Pattern Anal. Mach. Intell. 19(6), 580–593 (1997)CrossRef
19.
Hartley, R.: Lines and points in three views and the trifocal tensor. Int. J. Comput. Vis. 22(2), 125–140 (1997)CrossRef
20.
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, New York, NY, USA (2003)
21.
Heyden, A.: Projective structure and motion from image sequences using subspace methods. In: Scandinavian Conference on Image Analysis, pp. 963–968 (1997)
22.
Horn, B.K.P.: Closed-form solution of absolute orientation using unit quaternions. J. Opt. Soc. Am. 4(4), 629–642 (1987)CrossRefMathSciNet
23.
Kahl, F., Hartley, R.: Multiple-view geometry under the l\(\infty \)-norm. IEEE Trans. Pattern Anal. Mach. Intell. 30(9), 1603–1617 (2008)CrossRef
24.
Kang, S.B., Szeliski, R.: 3-d scene data recovery using omnidirectional multibaseline stereo. Int. J. Comput. Vis. 25, 167–183 (1997)CrossRef
25.
Ke, Q., Kanade, T.: Uncertainty models in quasiconvex optimization for geometric reconstruction. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. I: 1199–1205 (2006)
26.
Kim, J., Hartley, R.: Translation estimation from omnidirectional images. In: Proceedings of the Digital Image Computing on Techniques and Applications, pp. 22–27. IEEE Computer Society, Washington, DC, USA (2005)
27.
Lhuillier, M.: Automatic scene structure and camera motion using a catadioptric system. Comput. Vis. Image Underst. 109(2), 186–203 (2008)CrossRef
28.
Lim, J., Barnes, N., Li, H.: Estimating relative camera motion from the antipodal-epipolar constraint. IEEE Trans. Pattern Anal. Mach. Intell. 32(10), 1907–1914 (2010)CrossRef
29.
Longuet Higgins, H.: A computer algorithm for reconstructing a scene from two projections. Nature 293, 133–135 (1981)CrossRef
30.
Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef
31.
Ly, D.S., Demonceaux, C., Seulin, R., Fougerolle, Y.: Scale invariant line matching on the sphere. In: IEEE International Conference on Image Processing. Melbourne, Australia (2013)
32.
Ma, Y., Soatto, S., Kosecka, J., Sastry, S.: An Invitation to 3-D Vision: From Images to Geometric Models. Springer, Berlin (2005)
33.
Mahamud, S., Hebert, M.: Iterative projective reconstruction from multiple views. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. II: 430–437 (2000)
34.
Martinec, D., Pajdla, T.: Line reconstruction from many perspective images by factorization. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. I: 497–502 (2003)
35.
Martinec, D., Pajdla, T.: 3d reconstruction by fitting low-rank matrices with missing data. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. I: 198–205 (2005)
36.
Martinec, D., Pajdla, T.: Robust rotation and translation estimation in multiview reconstruction. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)
37.
Mei, C., Rives, P.: Single view point omnidirectional camera calibration from planar grids. In: International Conference on Robotics and Automation, pp. 3945–3950. Roma, Italy (2007)
38.
Micusik, B., Pajdla, T.: Structure from motion with wide circular field of view cameras. IEEE Trans. Pattern Anal. Mach. Intell. 28(7), 1135–1149 (2006)CrossRef
39.
Morris, D., Kanade, T.: A unified factorization algorithm for points, line segments and planes with uncertainty models. In: International Conference on Computer Vision, pp. 696–702 (1998)
40.
Nelson, R., Aloimonos, Y.: Finding motion parameters from spherical flow fields (or the advantages of having eyes in the back of your head). Biol. Cybern. 58, 261–273 (1988)CrossRef
41.
Nistér, D.: An efficient solution to the five-point relative pose problem. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 756–777 (2004)CrossRef
42.
Pollefeys, M., Van Gool, L., Vergauwen, M., Verbiest, F., Cornelis, K., Tops, J., Koch, R.: Visual modeling with a hand-held camera. Int. J. Comput. Vis. 59(3), 207–232 (2004)CrossRef
43.
Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C: The Art of Scientific Computing, 2nd edn. Cambridge University Press, New York, NY, USA (1992)
44.
Quan, L., Kanade, T.: Affine structure from line correspondences with uncalibrated affine cameras. IEEE Trans. Pattern Anal. Mach. Intell. 19(8), 834–845 (1997)CrossRef
45.
Quan, L., Lan, Z.: Linear n-point camera pose determination. IEEE Trans. Pattern Anal. Mach. Intell. 21(8), 774–780 (1999)
46.
Ramalingam, S., Lodha, S.K., Sturm, P.: A generic structure-from-motion framework. Comput. Vis. Image Underst. 103, 218–228 (2006)
47.
Rother, C.: Linear multi-view reconstruction of points, lines, planes and cameras, using a reference plane. In: International Conference on Computer Vision, pp. 1210–1217 (2003).
48.
Shakernia, O., Vidal, R., Sastry, S.: Omnidirectional egomotion estimation from back-projection flow. In: Workshop on Omnidirectional Vision and Camera Networks, pp. 82 (2003)
49.
Sim, K., Hartley, R.: Recovering camera motion using l-inf minimization. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. I: 1230–1237 (2006)
50.
Sturm, P., Triggs, B.: A factorization based algorithm for multi-image projective structure and motion. In: European Conference on Computer Vision, pp. II: 709–720 (1996)
51.
Svoboda, T.: Central panoramic cameras: Design, geometry, egomotion. Ph.D. thesis, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic (1999)
52.
Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. Int. J. Comput. Vis. 9(2), 137–154 (1992)CrossRef
53.
Torii, A., Imiya, A., Ohnishi, N.: Two- and three-view geometry for spherical cameras. In: Workshop on Omnidirectional Vision, Camera Networks and Non-classical cameras (2005).
54.
Triggs, B.: Factorization methods for projective structure and motion. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 845–851 (1996)
55.
Triggs, B.: Linear projective reconstruction from matching tensors. Image Vis. Comput. 15(8), 617–625 (1997)CrossRef
56.
Triggs, B.: Shape representation and recovery camera pose and calibration from 4 or 5 known 3d points. In: International Conference on Computer Vision, pp. 278–284 (1999)
57.
Triggs, B., McLauchlan, P., Hartley, R., Fitzgibbon, A.: Bundle adjustment: A modern synthesis. In: International Conference on Computer Vision Workshop Vision Algorithms, pp. 298–372 (1999)
58.
Vieville, T., Faugeras, O., Luong, Q.: Motion of points and lines in the uncalibrated case. Int. J. Comput. Vis. 17, 7–41 (1996)CrossRef
59.
Weng, J., Cohen, P., Herniou, M.: Camera calibration with distortion models and accuracy evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 14(10), 965–980 (1992)CrossRef
60.
Ying, X., Hu, Z.: Can we consider central catadioptric cameras and fisheye cameras within a unified imaging model. In: European Conference on Computer Vision, pp. I: 442–455 (2004)
61.
Zhang, Z., Shan, Y.: Incremental motion estimation through modified bundle adjustment. In: International Conference on Image Processing, pp. II: 343–346 (2003)
Metadaten
Titel
Extrinsic calibration of heterogeneous cameras by line images
verfasst von
Dieu Sang Ly
Cédric Demonceaux
Pascal Vasseur
Claude Pégard
Publikationsdatum
01.08.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 6/2014
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-014-0624-3

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