Abstract
This paper presents an approach of fusing the information provided by visible spectrum video with that of thermal infrared video to tackle video processing challenges such as object detection and tracking for increasing the performance and robustness of the surveillance system. An enhanced object detection strategy using gradient information along with background subtraction is implemented with efficient fusion based approach to handle typical problems in both the domains. An intelligent fusion approach using Fuzzy logic and Kalman filtering technique is proposed to track objects and obtain fused estimate according to the reliability of the sensors. Appropriate measurement parameters are identified to determine the measurement accuracy of each sensor. Experimental results are shown on some typical scenarios of detection and tracking of pedestrians.
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Conaire, C., Transfer, O.: report-Phd register: Thermal Infrared and Visible Spectrum Fusion for Multi-modal Video Analysis. Dublin City University, July 28 (2005)
Hu, W., Tan, T., Wang, L., Maybank., S.: A survey on visual surveillance of object motion and behaviors. IEEE Transactions on Systems, Man and Cybernetics 34(3), 334–350 (2004)
Cucchiara., R.: Multimedia surveillance systems. In: VSSN 2005: Proceedings of the third ACM international workshop on Video surveillance & sensor networks, New York, pp. 3–10 (2005)
Bhanu., B., Han., J.: Kinematic-based human motion analysis in infrared sequences. In: Proceedings Workshop Applications of Computer Vision, pp. 208–212 (2002)
Davis, J., Sharma, V.: Robust detection of people in thermal imagery. In: Proceedings of International Conference on Pattern Recognition, pp. 713–716 (2004)
McDaniel, R., Scribner, D., Krebs, W., Warren, P., Ockman, N., McCarley, J.: Image fusion for tactical applications. In: Proceedings of the SPIE - Infrared Technology and Applications XXIV, vol. 3436, pp. 685–695 (1998)
Torresan, H., Turgeon, B., Ibarra-Castanedo, C., Hébert, P., Maldague, X.: Advanced Surveillance Systems: Combining Video and Thermal Imagery for Pedestrian Detection. In: Proceedings of SPIE, Thermosense XXVI, SPIE, vol. 5405, pp. 506–515 (2004)
Davis, J., Sharma, V.: Fusion-Based Background-Subtraction using Contour Saliency. Computer Vision and Pattern Recognition, 20–26 (June 2005)
Snidaro, L., Niu, R., Varshney, P.K., Foresti, G.L.: Automatic camera selection and fusion for outdoor surveillance under changing weather conditions. In: IEEE Conference on Advanced Video and Signal based Surveillance, Florida, pp. 364–370 (2003)
Escamilla-Ambrosio, P.J., Mort, N.: A Hybrid Kalman Filter - Fuzzy Logic Architecture for Multisensor Data Fusion. In: Proceedings of the 2001 IEEE International Symposium on Intelligent Control, pp. 364–369 (2001)
Regazzoni, C., Ramesh, V., Foresti, G.L.: Special issue on video communications, processing, and understanding for third generation surveillance systems. Proceedings of the IEEE 89(10) (2001)
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© 2006 Springer-Verlag Berlin Heidelberg
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Kumar, P., Mittal, A., Kumar, P. (2006). Fusion of Thermal Infrared and Visible Spectrum Video for Robust Surveillance. In: Kalra, P.K., Peleg, S. (eds) Computer Vision, Graphics and Image Processing. Lecture Notes in Computer Science, vol 4338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949619_47
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DOI: https://doi.org/10.1007/11949619_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68301-8
Online ISBN: 978-3-540-68302-5
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