Automatic detection of calibration grids in time-of-flight images

Computer Vision and Image Understanding

Volumn 121, Issue , 2014, Pages 108-118

  Hansard, Miles ^a,b   Horaud, Radu ^a   Amat, Michel ^a   Evangelidis, Georgios ^a  

^a INRIA RHÔNE ALPES   (France)

^b QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

Camera calibration; Hough transform; Range imaging; Time of flight sensors

Indexed keywords

CAMERAS; HOUGH TRANSFORMS;

AUTOMATIC DETECTION; CAMERA CALIBRATION; DETECTION METHODS; GRADIENT VECTORS; HOUGH-BASED METHOD; RANGE IMAGING; TIME-OF-FLIGHT CAMERAS; TIME-OF-FLIGHT SENSORS;

CALIBRATION;

EID: 84897114646     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2014.01.007     Document Type: Article

References (41)

1. J.M. Dubois, H. Hügli, Fusion of time of flight camera point clouds, in: ECCV Workshop on Multi-Camera and Multi-modal Sensor Fusion Algorithms and Applications, 2008.
2. I. Schiller, C. Beder, R. Koch, Calibration of a PMD camera using a planar calibration object together with a multi-camera setup, in: Int. Arch. Soc. Photogrammetry, Remote Sensing and Spatial Information Sciences XXI, 2008, pp. 297-302.
3. J. Zhu, L. Wang, R.G. Yang, J. Davis, Fusion of time-of-flight depth and stereo for high accuracy depth maps, in: Proc. CVPR, 2008, pp. 1-8.
4. U. Hahne, M. Alexa, Depth imaging by combining time-of-flight and on-demand stereo, in: Proc. DAGM Workshop on Dynamic 3D Imaging, 2009, pp. 70-83.
5. R. Koch, I. Schiller, B. Bartczak, F. Kellner, K. Köser, MixIn3D: 3D mixed reality with ToF-camera, in: Proc. DAGM Workshop on Dynamic 3D Imaging, 2009, pp. 126-141.
6. A. Kolb, E. Barth, R. Koch, and R. Larsen Time-of-flight cameras in computer graphics Comput. Graph. Forum 29 1 2010 141 159
7. M. Hansard, R. Horaud, M. Amat, S. Lee, Projective alignment of range and parallax data, in: Proc. IEEE CVPR, 2011, pp. 3089-3096.
8. Z. Zhang A flexible new technique for camera calibration IEEE Trans. PAMI 22 11 2000 1330 1334
9. R. Hartley, and A. Zisserman Multiple View Geometry in Computer Vision 2000 Cambridge University Press
10. V. Douskos, I. Kalisperakis, G. Karras, E. Petsa, Fully automatic camera calibration using regular planar patterns, in: Int. Arch. Soc. Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37(5), 2008, pp. 21-26.
11. C. Harris, M. Stephens, A combined corner and edge detector, in: Proc. 4th Alvey Vision Conference, 1988, pp. 147-151.
12. L. Krüger, C. Wöhler, A. Würz-Wessel, F. Stein, In-factory calibration of multiocular camera systems, in: SPIE Photonics Europe, 2004, pp. 126-137.
13. Z. Wang, W. Wu, X. Xu, and D. Xue Recognition and location of the internal corners of planar checkerboard calibration pattern image Appl. Math. Comput. 185 2 2007 894 906
14. G. Bradski, and A. Kaehler Learning OpenCV 2008 O'Reilly
15. A. Datta, K. Jun-Sik, T. Kanade, Accurate camera calibration using iterative refinement of control points, in: Workshop on Visual Surveillance, Proc. ICCV 2009, 2009, pp. 1201-1208.
16. M. Lindner, I. Schiller, A. Kolb, and R. Koch Time-of-flight sensor calibration for accurate range sensing Comput. Vision Image Understan. 114 12 2010 1318 1328
17. B. Buttgen, and P. Seitz Robust optical time-of-flight range imaging based on smart pixel structures IEEE Trans. Circ. Syst. I: Regular Papers 55 6 2008 1512 1525
18. Mesa Imaging AG, Swiss Ranger, 2010. < http://www.mesa-imaging.ch/ >.
19. S. Foix, G. Alenya, and C. Torras Lock-in time-of-flight (ToF) cameras: a survey IEEE Sensors 11 9 2011 1917 1926
20. S.-J. Kim, J.D. Kim, B. Kang, and K. Lee A CMOS image sensor based on unified pixel architecture with time-division multiplexing scheme for color and depth image acquisition IEEE J. Solid-State Circ. 47 11 2012 2834 2844
21. C. Niclass, M. Soga, H. Matsubara, S. Kato, and M. Kagami A 100-m range 10-frame/s 340 96-pixel time-of-flight depth sensor in 0.18-CMOS IEEE J. Solid-State Circ. 48 2 2013 559 572
22. J.-E. Ha Automatic detection of calibration markers on a chessboard Opt. Eng. 46 10 2007 107203
23. J.-E. Ha Automatic detection of chessboard and its applications Opt. Eng. 48 6 2009 067205
24. S.T. Barnard Interpreting perspective images Artif. Intell. 21 1983 435 462
25. J.A. Shufelt Performance evaluation and analysis of vanishing point detection techniques IEEE Trans. Pattern Anal. Mach. Intell. 21 3 1999 282 288
26. L. Quan, and R. Mohr Determining perspective structures using hierarchical Hough transform Pattern Recogn. Lett. 9 4 1989 279 286
27. J. Košecká, and W. Zhang Video compass European Conference on Computer Vision 2006 Springer 476 490
28. R. Toldo, and A. Fusiello Robust multiple structures estimation with j-linkage European Conference on Computer Vision 2008 Springer 537 547
29. J.P. Tardif, Non-iterative approach for fast and accurate vanishing point detection, in: IEEE International Conference on Computer Vision, 2009, pp. 1250-1257.
30. M. Antunes, J.P. Barreto, A global approach for the detection of vanishing points and mutually orthogonal vanishing directions, in: IEEE Conference on Computer Vision and Pattern Recognition, 2013, pp. 1336-1343.
31. J. Illingworth, and J. Kittler A survey of the Hough transform Comput. Vision, Graph. Image Process. 44 1988 87 116
32. F. Bukhari, M. Dailey, Robust radial distortion from a single image, in: Proc. Int. Conf. on Advances in Visual Computing, 2010, pp. 11-20.
33. D. Gonzalez-Aguilera, J. Gomez-Lahoz, and P. Rodriguez-Gonzalvez An automatic approach for radial lens distortion correction from a single image IEEE Sensors 11 4 2011 956 965
34. R. Melo, M. Antunes, J. Barreto, G. Falcao, N. Gonçalves, Unsupervised intrinsic calibration from a single frame using a plumb-line approach, in: IEEE International Conference on Computer Vision, 2013, pp. 537-544.
35. A. de la Escalera, and J. Armingol Automatic chessboard detection for intrinsic and extrinsic camera parameter calibration Sensors 10 2010 2027 2044
36. T. Tuytelaars, M. Proesmans, L.V. Gool, The cascaded hough transform as support for grouping and finding vanishing points and lines, in: Proc. International Workshop on Algebraic Frames for the Perception-Action Cycle, 1997, pp. 278-289. (Pubitemid 127119208)
37. G. Granlund In search of a general picture processing operator Comput. Grap. Image Process. 8 1978 155 173 (Pubitemid 9397901)
38. M. Zhang, On the discretization of parameter domain in hough transformation, in: Proc. Int. Conf. on Pattern Recognition (ICPR), 1996, pp. 527-531.
39. L. Guo, and O. Chutatape Influence of discretization in image space on hough transform Pattern Recogn. 32 4 1999 635 644
40. H. Kälviäinen, P. Hirvonen, L. Xu, and E. Oja Probabilistic and non-probabilistic Hough transforms: overview and comparisons Image Vision Comput. 13 4 1995 239 252
41. L. Xu, E. Oja, and P. Kultanen A new curve detection method: randomized hough transform (rht) Pattern Recogn. Lett. 11 5 1990 331 338