Definition
The accurate and robust ROI detection and tracking in thermal faces can lead to better physiological monitoring. The calibration between RGB-D and thermal cameras allows fee body movements in practice, hel** to achieve such goals. This article presents two smart schemes to make the chessboard pattern with black and white squares visible to both cameras during the calibration process.
Introduction
The thermal infrared sensor (Gade and Moeslund 2014) is capable of recording small facial temperature variations because of its high sensitivity to thermal radiations emitted from the skin. Compared with traditional contact and wearable devices (Park et al. 2008; Storck et al. 1996), the thermal imaging process can be carried out in a contactless and unobtrusive way without discomfort. More importantly, the collected thermal data can be used to measure the physiological parameters such as the body temperature,...
References
Alkali, A.H., Saatchi, R., Elphick, H., Burke, D.: Facial tracking in thermal images for real-time noncontact respiration rate monitoring. In: Proceedings of the European Modelling Symposium, pp. 265–270 (2013)
Alkali, A.H., Saatchi, R., Elphick, H., Burke, D.: Short-time Fourier and wavelet transform analysis of respiration signal obtained by thermal imaging. In: Proceedings of the International Symposium on Communication Systems Networks and Digital Signal Processing, pp. 183–187 (2014)
Al-Khalidi, F., Saatchi, R., Burke, D., Elphick, H.: Tracking human face features in thermal images for respiration monitoring. In: Proceedings IEEE/ACS International Conference on Computer Systems and Applications, pp. 1–6 (2010)
Al-Khalidi, F., Saatchi, R., Elphick, H., Burke, D.: An evaluation of thermal imaging based respiration rate monitoring in children. American Journal of Engineering and Applied Sciences 4(4), 586–597 (2011)
Al-Khalidi, F., Saatchi, R., Elphick, H., Burke, D.: Tracing the region of interest in thermal human face for respiration monitoring. International Journal of Computer Applications 119(4), 42–46 (2015)
Chauvin, R., Hamel, M., Briere, S., Ferland, F., Grondin, F., Letourneau, D., Tousignant, M., Michaud, F.: Contact-free respiration rate monitoring using a pan-tilt thermal camera for stationary bike telerehabilitation sessions. IEEE Systems Journal 10(3), 1046–1055 (2016)
Chekmenev, S.Y., Farag, A.A., Essock, E.A.: Multiresolution approach for noncontact measurements of arterial pulse using thermal imaging. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop, pp. 129–136 (2006)
Chekmenev, S.Y., Farag, A.A., Essock, E.A.: Thermal imaging of the superficial temporal artery: An arterial pulse recovery model. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition pp. 1–6 (2007)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition vol. 1, pp. 886–893 (2005)
Dowdall, J., Pavlidis, I., Tsiamyrtzis, P.: Coalitional tracking. Computer Vision and Image Understanding 106(2–3), 205–219 (2007)
Fei, J., Pavlidis, I.: Thermistor at a distance: Unobtrusive measurement of breathing. IEEE Transactions on Biomedical Engineering 57(4), 988–998 (2010)
Fei, J., Zhu, Z., Pavlidis, I.: Imaging breathing rate in the CO2 absorption band. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 700–705 (2005)
FLIR ONE.: http://www.ir.com/irone (2018)
Fukunaga, K., Hostetler, L.: The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Transactions on Information Theory 21(1), 32–40 (1975)
Gade, R., Moeslund, T.B.: Thermal cameras and applications: A survey. Machine Vision and Applications 25(1), 245–262 (2014)
Garbey, M., Sun, N., Merla, A., Pavlidis, I.: Contact-free measurement of cardiac pulse based on the analysis of thermal imagery. IEEE Transactions on Biomedical Engineering 54(8), 1418–1426 (2007)
Kalal, Z., Mikolajczyk, K., Matas, J.: Face-TLD: Tracking-leaming-detection applied to faces. In: IEEE International Conference on Image Processing, pp. 3789–3792 (2010)
King, D.E.: Dlib-ml: A machine learning toolkit. Journal of Machine Learning Research 10, 1755–1758 (2009)
Lampo, T., Sierra, J., Chang, C.: Two algorithms for measuring human breathing rate automatically. In: Proceedings of the International Symposium on Visual Computing, pp. 686–697 (2009)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Proceedings of the International Joint Conferences on Artificial Intelligence, pp. 674–679 (1981)
Microsoft Kinect V1.: https://en.wikipedia.org/wiki/Kinect (2018)
Murthy, R., Pavlidis, I.: Noncontact measurement of breathing function. IEEE Engineering in Medicine and Biology Magazine 25(3), 57–67 (2006)
Murthy, J.N., van Jaarsveld, J., Fei, J., Pavlidis, I., Harrykissoon, R.I., Lucke, J.F., Faiz, S., Castriotta, R.J.: Thermal infrared imaging: A novel method to monitor airflow during polysomnography. Sleep. 32(11), 1521–1527 (2009)
Optris PI 450.: http://www.optris.com/thermal-imager-pi400 (2018)
Park, S.B., Noh, Y.S., Park, S.J., Yoon, H.R.: An improved algorithm for respiration signal extraction from electrocardiogram measured by conductive textile electrodes using instantaneous frequency estimation. Medical & Biological Engineering & Computing 46(2), 147–158 (2008)
Seek CompactPRO.: http://www.thermal.com/products/compactpro (2018)
Storck, K., Karlsson, M., Ask, P., Loyd, D.: Heat transfer evaluation of the nasal thermistor technique. IEEE Transactions on Biomedical Engineering 43(12), 1187–1191 (1996)
Sun, N., Garbey, M., Merla, A., Pavlidis, I.: Imaging the cardiovascular pulse. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition vol. 2, pp. 416–421 (2005)
Yang, M., Liu, Q., Turner, T., Wu, Y.: Vital sign estimation from passive thermal video. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition pp. 1–8 (2008)
Zhao, F., Cosar, S., Bellotto, N., Yue, S.: ROI detection and tracking for physiological monitoring based on calibration between RGB-D and thermal cameras. In: Proceedings of the Fifth International Conference on Interactive Digital Media, pp. 1–12 (2018)
Zhu, Z., Fei, J., Pavlidis, I.: Tracking human breath in infrared imaging. In: Proceedings of the IEEE Symposium on Bioinformatics and Bioengineering pp. 227–231 (2005)
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Zhao, F., Cosar, S., Bellotto, N., Yue, S. (2022). Smart Calibration between RGB-D and Thermal Cameras for ROI Detection and Tracking in Physiological Monitoring. In: Lee, N. (eds) Encyclopedia of Computer Graphics and Games. Springer, Cham. https://doi.org/10.1007/978-3-319-08234-9_373-1
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DOI: https://doi.org/10.1007/978-3-319-08234-9_373-1
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