[en] Many applications require the use of multiple cameras to cover a larger volume. In this paper, we evaluate several pair-wise calibration techniques dedicated to range cameras. We compare the precision of a self-calibration technique based on the movement in front of the cameras to object based calibration. While the self-calibration method is less precise than its counterparts, it yields a first estimation of the transformation between the cameras and permits to detect when the cameras become mis-aligned. Therefore it is useful in a practical situations.
Centre/Unité de recherche :
INTELSIG
Disciplines :
Ingénierie électrique & électronique
Auteur, co-auteur :
Lejeune, Antoine ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images
Grogna, David ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images
Van Droogenbroeck, Marc ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Verly, Jacques ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images
Langue du document :
Anglais
Titre :
Evaluation of pairwise calibration techniques for range cameras and their ability to detect a misalignment
D. Alexiadis, D. Zarpalas, and P. Daras. Real-time, full 3-D reconstruction of moving foreground objects from multiple consumer depth cameras. IEEE Transactions on Multimedia, 15(2):339-358, February 2013
A. Azarbayejani and A. Pentland. Real-time selfcalibrating stereo person tracking using 3-D shape estimation from blob features. In IEE E International Conference on Pattern Recognition (ICPR), volume 3, pages 627-632, August 1996
G. Bradski. The OpenCV Library. Dr. Dobb's Journal of Software Tools, 2000
A. Butler, S. Izadi, O. Hilliges, D. Molyneaux, S. Hodges, and D. Kim. Shake'n'sense: Reducing interference for overlapping structured light depth cameras. In SIGCHI Conference on Human Factors in Computing Systems, CHI '12, pages 1933-1936, New York, NY, USA, May 2012. ACM
V. Castaneda. Constructive interference for Multi-view Time-of-Flight acquisition. PhD thesis, Technische Universitat München, 2012
X. Chen, J. Davis, and P. Slusallek. Wide area camera calibration using virtual calibration objects. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), volume 2, pages 520-527, June 2000
M. Frank, M. Plaue, H. Rapp, U. Kothe, B. Jahne, and F. Hamprecht. Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras. Optical Engineering, 48(1), January 2009
B. Freedman, A. Shpunt, M. Machline, and Y. Arieli. Depth mapping using projected patterns, 2010. US Patent Application 20100118123.
D. Glas, T. Miyashita, H. Ishiguro, and N. Hagita. Automatic position calibration and sensor displacement detection for networks of laser range finders for human tracking. In IEEE/RSJ International Confere nce on Intelligent Robots and Systems (IROS), pages 2938-2945, Taipei, Taiwan, October 2010
R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, second edition, 2004
D. Huynh. Metrics for 3d rotations: Comparison and analysis. Journal of Mathematical Imaging and Vision, 35(2):155-164, 2009
S. Izadi, R. Newcombe, D. Kim, O. Hilliges, D. Molyneaux, S. Hodges, P. Kohli, A. Davison, and A. Fitzgibbon. KinectFusion: Real-ti me dynamic 3D surface reconstruction and interaction. In ACM SIGGRAPH Talks, Vancouver, Canada, 2011
S. Kaenchan, P. Mongkolnam, B. Watanapa, and S. Sathienpong. Automatic multiple kinect cameras setting for simple walking posture analysis. In International Computer Science and Engineering Conference (ICSEC), pages 245-249, September 2013
K. Khoshelham and S. Elberink. Accuracy and resolution of Ki nect depth data for indoor mapping applications. Sensors, 12(2):1437-1454, February 2012
M. Lindner, I. Schiller, A. Kolb, and R. Koch. Timeof-Flight sensor calibration for accurate range sensing. Computer Vision and Image Understanding, 114(12):1318- 1328, 2010
L. Markley. Attitude determination using vector observations and the singular value decomposition. The Journal of the Astronautical Sciences, 36(3):245-258, July 1988
S. Pié rard, R. Phan-Ba, V. Delvaux, P. Maquet, and M. Van Droogenbroeck. GAIMS: a powerful gait analysis system satisfying the c onstraints of clinical routine. Multiple Sclerosis Journal, 19(S1):359, October 2013. Proceedings of ECTRIMS/RIMS 2013 (Copenhagen, Denmark), P800
S. Rusinkiewicz and M. Levoy. Efficient variants of the ICP algorithm. In International Conference on 3D Digital Imaging and Modeling (3DIM), pages 145-152, Quebec City, Canada, June 2001
Y. Schrö der, A. Scholz, K. Berger, K. Ruhl, S. Guthe, and M. Magnor. Multiple Kinect studies. Technical Report 09-15, ICG, October 2011
J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake. Real-time human pose recognition in parts from single depth images. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pages 1297-1304, Providence, Rhode Island , USA, June 2011
T. Svoboda, D. Martinec, and T. Pajdla. A convenient multi-camera self-calibration for virtual environments. PRESENCE: Teleoperators and Virtual Environments, 14(4):407-422, August 2005
Z. Xu, R. Schwarte, H. Heinol, B. Buxbaum, and T. Ringbeck. Smart pixel-photonic mixer device (PMD): New system concept of a 3D-imaging camera-on-a-chip. In International Conference on Mechatronics and Machine Vision in Practice (M2VIP), pages 259-264, Nanjing, China, September 1998
