Abstract
In this paper, we proposed a novel method of geometric calibration and synchronization for a multi camera system. Traditional calibration methods of visible cameras can’t be applied to thermal cameras. According to the imaging characteristics of thermal cameras, we designed a new calibration board using materials with different emissivity for calibration. Our calibration board can accurately calibrate RGBD cameras and thermal cameras. In general, thermal cameras have regular non-uniformity corrections, which will result in camera interruption about 1.5 to 2 s and can impact synchronization. In this respect, we adopted the method named nearest adjacent time using timestamp to solve the problem of non-uniformity corrections and synchronization. We evaluated our methods and the experiments showed that our methods had an ideal result for camera calibration and synchronization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zennaro, S., Munaro, M., Milani, S., Zanuttigh, P., Bernardi, A., Ghidoni, S., et al.: Performance evaluation of the 1st and 2nd generation Kinect for multimedia applications. In: International Conference on Multimedia and Expo, pp. 1–6. IEEE, Turin (2015)
Butkiewicz, T.: Low-cost coastal mapping using Kinect v2 time-of-flight cameras. In: Oceans, pp. 1–9. IEEE, St. John’s (2015)
Gonzalez-Jorge, H., Rodríguez-Gonzálvez, P., Martínez-Sánchez, J., González-Aguilera, D., Arias, P., Gesto, M., et al.: Metrological comparison between kinect I and kinect II sensors. Measurement 70, 21–26 (2015)
Corti, A., Giancola, S., Mainetti, G., Sala, R.: A metrological characterization of the Kinect V2 time-of-flight camera. Robot. Auton. Syst. 75(8), 584–594 (2015)
Lachat, E., Macher, H., Landes, T., Grussenmeyer, P.: Assessment and calibration of a RGB-D camera (Kinect v2 Sensor) towards a potential use for close-range 3D modeling. Remote Sens. 7(10), 13070–13097 (2015)
Moghadam, P., Vidas, S., Lam, O.: Spectra: 3D multispectral fusion and visualization toolkit. In: Australasian Conference on Robotics and Automation. ACRA, Melbourne (2014)
Borrmann, D., Nüchter, A., Djakulovi’C, M., Maurovi’C, I., Petrovi’C, I., Osmankovi’C, D., et al.: The Project thermalmapper-thermal 3D mapping of indoor environments for saving energy. Ifac Symp. Robot. Control 45(22), 31–38 (2012)
Nauer, C., Vonach, E., Gerstweiler, G., Kaufmann, H.: 3D building reconstruction and thermal mapping in fire brigade operations. In: Augmented Human International Conference, pp. 1–2. IEEE, Lake Buena Vista (2013)
Borrmanna, D., Nüchtera, A., Ðakulovic, M., Maurovic, I., Petrovic, I., Osmankovic, O., et al.: A mobile robot based system for fully automated thermal 3D mapping. Adv. Eng. Inform. 28(4), 425–440 (2014)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)
Vidas, S., Moghadam, P., and Bosse, M. (2013).: 3D thermal mapping of building interiors using an RGB-D and thermal camera. In: International Conference on Robotics and Automation, pp. 2311–2318. IEEE, Karlsruhe (2013)
Lussier, J. T., Thrun, S.: Automatic calibration of RGBD and thermal cameras. In: International Conference on Intelligent Robots and Systems, pp. 451–458. IEEE, Chicago (2014)
Skala, K., Lipić, T., Sović, I., Gjenero, L., Grubišić, I.: 4D thermal imaging system for medical applications. Periodicum Biologorum 113(4), 407–416 (2011)
Ham, Y., Golparvar-Fard, M.: An automated vision-based method for rapid 3D energy performance modeling of existing buildings using thermal and digital imagery. Adv. Eng. Inform. 27(3), 395–409 (2013)
Kim, N., Choi, Y., Hwang, S., Park, K.: Geometrical calibration of multispectral calibration. In: International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 384–385. IEEE, Goyang (2015)
Gschwandtner, M., Kwitt, R., Uhl, A., Pree, W.: Infrared camera calibration for dense depth map construction. In: Intelligent Vehicles Symposium, pp. 857–862. IEEE, Baden-Baden (2011)
St-Laurent, L., Prévost, D., Maldague, X.: Fast and accurate calibration-based thermal/color sensors registration. In: 10th International Conference on Quantitative Infrared Thermography, QIRT, Québec, Canada, pp. 27–30 (2010)
Hwang, S., Choi, Y., Kim, N., Park, K.: Low-cost synchronization for multispectral cameras. In: International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 435–436. IEEE, Goyang (2015)
Baar, J.V., Beardsley, P., Pollefeys, M., Gross, M.: Sensor fusion for depth estimation, including TOF and thermal sensors. In: 2nd International Conference on 3d Imaging, Modeling, Processing, Visualization and Transmission, pp. 472–478. IEEE, Zurich (2012)
Miller, S., Teichman, A., Thrun, S.: Unsupervised extrinsic calibration of depth sensors in dynamic scenes. In: Intelligent Robots and Systems, pp. 2695–2702. IEEE, Tokyo (2013)
Datta, A., Kim, J.S., Kanade, T.: Accurate camera calibration using iterative refinement of control points. In: 12th Computer Vision Workshops, pp. 1201–1208. IEEE, Kyoto (2009)
Bahnsen, C.: Thermal-visible-depth image registration (2017). http://projekter.aau.dk/projekter/en/studentthesis/termiskvisueldybde-billedregistering(8564c183-bdc1-4a9c-8bda-c71878cb0814).html
Acknowledgments
This work is supported by National Nature Science Foundation under Grant No. 61573144, 61502293 and 61205017.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Han, S., Gu, X., Gu, X. (2017). An Accurate Calibration Method of a Multi Camera System. In: Fei, M., Ma, S., Li, X., Sun, X., Jia, L., Su, Z. (eds) Advanced Computational Methods in Life System Modeling and Simulation. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-6370-1_49
Download citation
DOI: https://doi.org/10.1007/978-981-10-6370-1_49
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-6369-5
Online ISBN: 978-981-10-6370-1
eBook Packages: Computer ScienceComputer Science (R0)