Calibración de cámaras de tiempo de vueloAjuste adaptativo del tiempo de integración y análisis de la frecuencia de modulación

  1. P. Gil 1
  2. T. Kisler 2
  3. G.J. García 1
  4. C.A. Jara 1
  5. J.A. Corrales 1
  1. 1 Universitat d'Alacant
    info

    Universitat d'Alacant

    Alicante, España

    ROR https://ror.org/05t8bcz72

  2. 2 Technical University Munich
    info

    Technical University Munich

    Múnich, Alemania

    ROR https://ror.org/02kkvpp62

Revista:
Revista iberoamericana de automática e informática industrial ( RIAI )

ISSN: 1697-7920

Ano de publicación: 2013

Volume: 10

Número: 4

Páxinas: 453-464

Tipo: Artigo

DOI: 10.1016/J.RIAI.2013.08.002 DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: Revista iberoamericana de automática e informática industrial ( RIAI )

Resumo

La percepción de profundidad se hace imprescindible en muchas tareas de manipulación, control visual y navegación de robots. Las cámaras de tiempo de vuelo (ToF: Time of Flight) generan imágenes de rango que proporcionan medidas de profundidad en tiempo real. No obstante, el parámetro distancia que calculan estas cámaras es fuertemente dependiente del tiempo de integración que se configura en el sensor y de la frecuencia de modulación empleada por el sistema de iluminación que integran. En este artículo, se presenta una metodología para el ajuste adaptativo del tiempo de integración y un análisis experimental del comportamiento de una cámara ToF cuando se modifica la frecuencia de modulación. Este método ha sido probado con éxito en algoritmos de control visual con arquitectura ‘eye-in-hand’ donde el sistema sensorial está compuesto por una cámara ToF. Además, la misma metodología puede ser aplicada en otros escenarios de trabajo.

Referencias bibliográficas

  • Bouguet, J. Y., 2000. Pyramidal implementation of affine Lucas Kanade feature tracker. Intel Corporation- Microprocessor Research Labs, OpenCV Library.
  • Chaumette, F., Hutchinson, S., 2006. Visual servo control. I. Basic approaches. IEEE Robotics and Automation Magazine 13, IEEE Press, pp. 82-90.
  • Chiabrando, F., Chiabrando, R., Piatti, D., Rianudo, F., 2009. Sensors for 3d imaging: metric evualuation an calibration of CCD/CMOS time-of-flight camera. Sensors 9(9), pp. 10080-10096. DOI: 10.3390/s91210080
  • Distante, C., Diraco, G., Leone, A., 2010. Active range imaging dataset for indoor surveillance. In Proc. of British Machine Vision Conference (BMVC), BMVA Press, vol. 2, pp.1-16.
  • Foix, S., Aleny, G., Torras, C., 2011. Lock-in time-of-flight (ToF) cameras: a survey. IEEE Sensors Journal 11(3), pp. 1917-1926. DOI: 10.1109/JSEN.2010.2101060
  • Frank, M., Plaue, M., Rapp, H., Köthe, U., Jähne, B., Hamprecht, F.A., 2009. Theoretical and experimental error analysis of continous-wave time-offlight range cameras. Optical Engineering 48(1), pp. 13602-13618.
  • Fuchs, S. Hirzinger, G., 2008. Extrinsic and depth calibration of ToF-cameras. In Proc. of Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Press Society, pp. 1-6. DOI: 10.1109/CVPR.2008.4587828
  • Garcia, F., Aouada D., Mirbach, B., Solignac T., Ottersten B., 2011. Real-time hybrod ToF multi-camera rig fusion system for depth map enhancement. In Proc. of Co DOI: 10.1109/CVPRW.2011.5981740
  • Gil, P., Pomares, J., Torres, F., 2010. Analysis and adaptation of integration time in PMD camera for visual servoing. In Proc. of 20th International Conference on Pattern Recognition (ICPR), IEEE Press Society, pp. 311- 315. DOI: 10.1109/ICPR.2010.85
  • Herrera, D.C., Kannala, J., Heikkila, J., 2011. Accurate and practical calibration of a depth and color camera pair. In Proc. of 14th International Conference on Computer Analysis of Images and Patterns (CAIP), vol 2, Ed. Springer-Verlag Berlín, Heidelberg, pp. 437-445.
  • Hussman, S., Liepert, T., 2009. Three-dimensional tof robot vision system. IEEE Transactions on Instrumentation and Measurement 58(1), pp. 141- 146. DOI: 10.1109/TIM.2008.928409
  • Hussman, S., Edeler, T., 2010. Robot vision using 3d tof systems. En: Ales Ude (Ed.), Robot Vision. Intech Press, pp. 293-306.
  • Kakiuchi, Y., Ueda, R., Kobayashi, K., Okada, K., Inaba, M., 2010. Working with movable obstacles using on-line environmet perception reconstruction using active sensing and color range sensor. In Proc. of International Conference on Intelligent Robots and Systems (IROS), IEEE Press, pp. 1696-1701. DOI: 10.1109/IROS.2010.5650206
  • Kim, Y.M., Chan, D., Theobalt, C., Thrun, S., 2008. Design and calibration of a multi-view ToF sensor fusion system. In Proc. of 22nd Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Press Society, pp. 1524-1530. DOI: 10.1109/CVPRW.2008.4563160
  • Kisler, T., Gil, P., 2011. Detección y seguimiento de objetos sólidos con cámaras ToF. Actas de XXXII Jornadas de Automática (JA), CEA-IFAC Actas. Sevilla (Spain).
  • Khoshelham, K. 2011. Accuracy analysis of Kinect depth data. En: D.D. Lichti and A.F. Habbib (Ed.). In Proc of ISPRS Journal of Photogrammetry and Remote Sensing-Workshop on Laser Scanning, vol. 38(5), pp. 29-31.
  • Kolb, A., Barth, E., Koch, E., Larse, R., 2010. Time-of-flight Cameras in Computer Graphics. Computer Graphics Forum, vol. 29(1), pp. 141-159. DOI: 10.1111/j.1467-8659.2009.01583.x
  • Kuehnle, J.U., Xue, Z., Sotz, M., Zoellner, J.M., Verl, A., Dillmann, R., 2008. Grasping in depth maps of time-of-flight cameras. In Proc. of IEEE International Workshop on Robotic and Sensors Environments (ROSE). pp. 132-137. DOI: 10.1109/ROSE.2008.466914
  • Lai, K., Liefeng Bo, Xiaofrng Ren, Fox, D., 2011. Spares distance learning for object recognition combining RGB and depth information. In Proc. of International Conference on Robotics and Automation (ICRA), IEEE Press Society, pp. 4007-4013. DOI: 10.1109/ICRA.2011.5980377
  • Lichti, D., 2008. Self-calibration of a 3D range camera. In Proc of International Society for Photogrammetry and Remote Sensing 37(3), pp.1-6
  • Lichti, D. Rouzaud, D., 2009. Surface-dependent 3d range camera selfcalibration. En: A Beraldin, G.S. Cheok, M. McCarthy (Ed.), In Proc. of SPIE vol. 72390, pp . DOI: 10.1117/12.805509
  • Lichti, D., Kim, C., 2011. A comparison of three geometric self-calibration methods for range cameras. Remote Sensing 11(3), pp. 1014-1028. DOI: 10.3390/rs3051014
  • Lindner, M., Kolb, A., Ringbeck, T., 2008. New insights into the calibration of ToF-sensors. In Proc. of 22nd Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Press Society, pp. 1603-1607. DOI: 10.1109/CVPRW.2008.4563172
  • Lindner, M., Schiller, I., Kolb, A., Koch, R., 2010. Time-of-flight sensor calibration for accurate range sensing. Computer Vision and Image Understanding vol. 114(2), pp. 1318-1328. DOI: 10.1016/J.CVIU.2009.11.002
  • May, S., Werner, B., Surmann, H., Pervölz, K., 2006. “3d time-of-flight cameras for mobile robotics. In Proc. of International Conference on Intelligent Robots and Systems (IROS), IEEE Press, 790-795, DOI: 10.1109/IROS.2006.281670
  • May, S., Fuchs, S., Droeschel, D. Holz, D., Nüchter, A., 2009. Robust 3dmapping with time-of-flight cameras. In Proc. of International Conference on Intelligent Robots and Systems (IROS), IEEE Press Society, pp 1673- 1678.
  • May, S., Droeschel, D., Holz, D., Fuchs, S., Malis, E., Nüchter, A., Hertzberg, J., 2009. Three-dimensional mapping with time-of-light cameras. Journal of Field Robotics. Special Issue on Three-dimensional Mapping Part 2, 26(11-12), pp. 934-965. DOI: 10.1002/ROB.20321
  • Mufti, F., Mahony, R., 2011. Statistical analysis of signal measurement in time of flight cameras. Journal of Photogrammetry and Remote Sensing (ISPR) vol. 66(5), pp. 720-731. DOI: 10.1016/J.ISPRSJPR.2011.06.004
  • Pattison, T., 2010. Quantification and description of distance measurement errors of a time-of-flight camera. M.Sc. Thesis. University of Stuttgart, Stuttgart (Germany).
  • Pomares, J., Gil, P., Torres, F., 2010. Visual control of robots using range images. Sensors 10(8), pp. 7303-7322. DOI: 10.3290/s100807303
  • Rapp, H., Frank, M., Hamprecht, F.A., Jähne, B., 2008. A theoretical and experimental investigation of the systematic errors and statistical uncertainties of time-of-flight-cameras. International Journal of Intelligent Systems Technologies and Applications vol. 5(3-4), pp. 402-413. DOI: 10.1504/IJISTA.2008.021303
  • Shahbazi, M., Hoimayouni, S., Saadatseresht, M., Sattari, M., 2011. Range camera self-calibration based on integrated bundle adjustment via joint setup with a 2d digital camera. Sensors 11(11), pp. 8721-8740. DOI: 10.3290/s110908721
  • Schaller, C., 2011, Time-of-Flight-A new Modality for Radiotherapy, M.Sc. Thesis. University Erlangen-Nuremberg, Erlagen (Germany).
  • Schiller, I., Beder, C., Koch, R., 2008. Calibration of a PMD-camera using a planar calibration pattern together with a multi-camera setup. In Proc. of ISPRS Journal of Photogrammetry and Remote Sensing vol. 37, pp. 297- 302.
  • Schwarz, L., Mateus, D., Castaneda, V., Navab, N., 2010. Manifold learning for ToF-based human body tracking and activity recognition. In Proc. of British Machine Vision Conference (BMVC), BMVA Press, pp.1-11. DOI: 10.5244/C.24.80
  • Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A., 2011. Real-time human pose recognition in parts from single depth images. In Proc of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Press Society, pp. 1297- 1304.
  • Smisek, J., 2011. 3D Camera Calibration. MSc. Thesis. Czech Technnical Univesity, Prague (Czech).
  • Weyer, C.A., Bae, K.H., Lim, K., Lichti, D., 2008. Extensive metric performance evaluation of a 3D range camera. In Proc. of ISPRS Journal of Photogrammetry and Remote Sensing vol.37(5), pp.939-944.
  • Wiedemann M., Sauer M., Driewer F. Schilling K., 2008. Analysis and characterization of the PMD camera for aplication in mobile robots. M. J. Chung and P. Misra (Ed.). In Proc. of 17th World Congress of the International Federation of Automotic Control, IFAC Press, pp.13689- 13694.
  • Zhang, Z., 2000. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(11), pp. 1330-1334. DOI: 10.1109/34.888718
  • Zhu, J., Wang, L., Yang, R., Davis, J., 2008. Fusion of time-of-flight depth and stereo for high accuracy depth maps. In Proc. of Computer Vision and Pattern Recognition (CVPR), IEEE Press Society, pp. 1-8. DOI: 10.1109/CVPR.2008.4587761
  • Zhu, J., Yang, R., Xiang, X., 2011. Eye contact in video conference via fusion of time-of-flight depth sensor and stereo. 3D Research 2(3), pp. 1-10. DOI: 10.1007/3Dres.03(2011)5
  • Zinber, T., Schmidt, J., Niemann, H., 2003. A refined ICP algorithm for robust 3d correspondence estimation. In Proc. of Conference on Image Processing (ICIP), IEEE Press, pp. 695-698.