Abstract
Current Time-of-Flight approaches mainly incorporate an continuous wave intensity modulation approach. The phase reconstruction is performed using multiple phase images with different phase shifts which is equivalent to sampling the inherent correlation function at different locations. This active imaging approach delivers a very specific set of influences, on the signal processing side as well as on the optical side, which all have an effect on the resulting depth quality. Applying ToF information in real application therefore requires to tackle these effects in terms of specific calibration approaches. This survey gives an overview over the current state of the art in ToF sensor calibration.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Lange, R.: 3D Time-of-Flight Distance Measurement with Custom Solid-State Image Sensor in CMOS/CCD-Technology. PhD thesis (2000)
Davis, J., Gonzalez-Banos, H.: Enhanced shape recovery with shuttered pulses of light. In: Pulses of Light? IEEE Workshop on Projector-Camera Systems (2003)
Rapp, H.: Experimental and theoretical investigation of correlating tof-camera systems. Master’s thesis (2007)
Schmidt, M., Jähne, B.: A physical model of time-of-flight 3D imaging systems, including suppression of ambient light. In: Kolb, A., Koch, R. (eds.) Dyn3D 2009. LNCS, vol. 5742, pp. 1–15. Springer, Heidelberg (2009)
Dorrington, A.A., Cree, M.J., Carnegie, D.A., Payne, A.D., Conroy, R.M., Godbaz, J.P., Jongenelen, A.P.: Video-rate or high-precision: A flexible range imaging camera. In: Electronic Imaging 2008, International Society for Optics and Photonics, pp. 681307–681307 (2008)
Lindner, M., Kolb, A.: Lateral and depth calibration of pmd-distance sensors. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Nefian, A., Meenakshisundaram, G., Pascucci, V., Zara, J., Molineros, J., Theisel, H., Malzbender, T. (eds.) ISVC 2006. LNCS, vol. 4292, pp. 524–533. Springer, Heidelberg (2006)
Schiller, I., Beder, C., Koch, R.: Calibration of a pmd camera using a planar calibration object together with a multi-camera setup. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Part B3a, Beijing, China, vol. XXXVII, pp. 297–302 XXI. ISPRS Congress (2008)
Payne, A.D., Dorrington, A.A., Cree, M.J., Carnegie, D.A.: Improved measurement linearity and precision for amcw time-of-flight range imaging cameras. Applied Optics 49(23), 4392–4403 (2010)
Lindner, M.: Calibration and Real-Time Processing of Time-of-Flight Range Data. PhD thesis, CG, Fachbereich Elektrotechnik und Informatik, Univ. Siegen (2010)
Schmidt, M.: Analysis, Modeling and Dynamic Optimization of 3D Time-of-Flight Imaging Systems. PhD thesis, IWR, Fakultät für Physik und Astronomie, Univ. Heidelberg (2011)
Godbaz, J.P.: Ameliorating systematic errors in full-field AMCW lidar. PhD thesis, School of Engineering, University of Waikato, Hamilton, New Zealand (2012)
A., G.S., Aanaes, H., Larsen, R.: Environmental effects on measurement uncertainties of time-of-flight cameras. In: Proceedings of International Symposium on Signals, Circuits and Systems 2007, ISSCS 2007 (2007)
Shack, R.V.: Characteristics of an image-forming system. Journal of Research of the National Bureau of Standards 56(5), 245–260 (1956)
Barakat, R.: Application of the sampling theorem to optical diffaction theory. Journal fo the Optical Society of America 54(7) (1964)
Saleh, B.E.A., Teich, M.C.: 10. In: Fundamentals of Photonics, pp. 368–372. John Wiley and Sons, New York (1991)
Matsuda, S., Nitoh, T.: Flare as applied to photographic lenses. Applied Optics 11(8), 1850–1856 (1972)
Godbaz, J., Cree, M., Dorrington, A.: Understanding and ameliorating non-linear phase and amplitude responses in amcw lidar. Remote Sensing 4(1) (2012)
Seitz, P.: Quantum-noise limited distance resolution of optical range imaging techniques. IEEE Transactions on Circuits and Systems I: Regular Papers 55(8), 2368–2377 (2008)
Erz, M., Jähne, B.: Radiometric and spectrometric calibrations, and distance noise measurement of toF cameras. In: Kolb, A., Koch, R. (eds.) Dyn3D 2009. LNCS, vol. 5742, pp. 28–41. Springer, Heidelberg (2009)
Frank, M., Plaue, M., Rapp, H., Köthe, U., Jähne, B., Hamprecht, F.A.: Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras. Optical Engineering 48(1), 13602 (2009)
Emva standard 1288 -standard for measurement and presentation of specifications for machine vision sensors and cameras, Release 3.0 (2010)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)
Beder, C., Bartczak, B., Koch, R.: A comparison of PMD-cameras and stereo-vision for the task of surface reconstruction using patchlets. In: IEEE/ISPRS BenCOS Workshop 2007 (2007)
Streckel, B., Koch, R.: Lens model selection for visual tracking. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds.) DAGM 2005. LNCS, vol. 3663, pp. 41–48. Springer, Heidelberg (2005)
Kahlmann, T., Remondino, F., Ingensand, H.: Calibration for increased accuracy of the range imaging camera swissrangertm. In: Proc. of IEVM (2006)
Beder, C., Koch, R.: Calibration of focal length and 3d pose based on the reflectance and depth image of a planar object. In: Proceedings of the DAGM Dyn3D Workshop, Heidelberg, Germany (2007)
Marvin, L., Ingo, S., Andreas, K., Reinhard, K.: Time-of-flight sensor calibration for accurate range sensing. Comput. Vis. Image Underst. 114(12), 1318–1328 (2010)
Lindner, M., Kolb, A.: Calibration of the intensity-related distance error of the pmd tof-camera. In: Proc. SPIE, Intelligent Robots and Computer Vision, vol. 6764, p. 67640W (2007)
Steiger, O., Felder, J., Weiss, S.: Calibration of time-of-flight range imaging cameras. In: 15th IEEE International Conference on Image Processing, ICIP 2008, pp. 1968–1971. IEEE (2008)
Swadzba, A., Beuter, N., Schmidt, J., Sagerer, G.: Tracking objects in 6d for reconstructing static scenes. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2008, pp. 1–7. IEEE (2008)
Reynolds, M., Dobos, J., Peel, L., Weyrich, T., Brostow, G.J.: Capturing time-of-flight data with confidence. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 945–952. IEEE (2011)
Lindner, M., Lambers, M., Kolb, A.: Sub-pixel data fusion and edge-enhanced distance refinement for 2d / 3d images. International Journal of Intelligent Systems Technologies and Applications 5, 344–354 (2008)
Pathak, K., Birk, A., Poppinga, J.: Sub-pixel depth accuracy with a time of flight sensor using multimodal gaussian analysis. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2008, pp. 3519–3524 (2008)
Moser, B., Bauer, F., Elbau, P., Heise, B., Schöner, H.: Denoising techniques for raw 3D data of ToF cameras based on clustering and wavelets. In: Proc. SPIE, vol. 6805 (2008)
H., S., Moser, B., Dorrington, A.A., Payne, A., Cree, M.J., Heise, B., Bauer, F.: A clustering based denoising technique for range images of time of flight cameras. In: CIMCA/IAWTIC/ISE 2008, pp. 999–1004 (2008)
Schuon, S., Theobalt, C., Davis, J., Thrun, S.: Lidarboost: Depth superresolution for tof 3d shape scanning. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 343–350. IEEE (2009)
Cui, Y., Schuon, S., Chan, D., Thrun, S., Theobalt, C.: 3d shape scanning with a time-of-flight camera. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 1173–1180. IEEE (2010)
Lindner, M., Kolb, A.: Compensation of motion artifacts for time-of-flight cameras. In: Kolb, A., Koch, R. (eds.) Dyn3D 2009. LNCS, vol. 5742, pp. 16–27. Springer, Heidelberg (2009)
Erz, M.: Charakterisierung von Laufzeit-Kamera-Systemen für Lumineszenz- Lebensdauer-Messungen. PhD thesis, IWR, Fakultät für Physik und Astronomie, Univ. Heidelberg (2011)
Gokturk, S.B., Yalcin, H., Bamji, C.: A time-of-flight depth sensor-system description, issues and solutions. In: Conference on Computer Vision and Pattern Recognition Workshop, CVPRW 2004, pp. 35–35. IEEE (2004)
Lottner, O., Sluiter, A., Hartmann, K., Weihs, W.: Movement artefacts in range images of time-of-flight cameras. In: International Symposium on Signals, Circuits and Systems, ISSCS 2007, vol. 1, pp. 1–4. IEEE (2007)
Hussmann, S., Hermanski, A., Edeler, T.: Real-time motion artifact suppression in tof camera systems. IEEE Transactions on Instrumentation and Measurement 60, 1682–1690 (2011)
Hansard, M., Lee, S., Choi, O., Horaud, R.P.: Time of Flight Cameras: Principles, Methods, and Applications. SpringerBriefs in Computer Science. Springer (2012)
Sturmer, M., Penne, J., Hornegger, J.: Standardization of intensity-values acquired by time-of-flight-cameras. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2008, pp. 1–6. IEEE (2008)
Zach, C., Pock, T., Bischof, H.: A duality based approach for realtime tv-l 1 optical flow. In: Hamprecht, F.A., Schnörr, C., Jähne, B. (eds.) DAGM 2007. LNCS, vol. 4713, pp. 214–223. Springer, Heidelberg (2007)
Lefloch, D., Hoegg, T., Kolb, A.: Real-time motion artifacts compensation of tof sensors data on gpu. In: Proc. SPIE, Three-Dimensional Imaging, Visualization, and Display, vol. 8738. SPIE (2013)
Dorrington, A.A., Godbaz, J.P., Cree, M.J., Payne, A.D., Streeter, L.V.: Separating true range measurements from multi-path and scattering interference in commercial range cameras (2011)
Godbaz, J.P., Cree, M.J., Dorrington, A.A.: Closed-form inverses for the mixed pixel/multipath interference problem in AMCW lidar (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Lefloch, D. et al. (2013). Technical Foundation and Calibration Methods for Time-of-Flight Cameras. In: Grzegorzek, M., Theobalt, C., Koch, R., Kolb, A. (eds) Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications. Lecture Notes in Computer Science, vol 8200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44964-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-44964-2_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-44963-5
Online ISBN: 978-3-642-44964-2
eBook Packages: Computer ScienceComputer Science (R0)