Abstract
This paper presents a scheme for object detection and tracking in heterogeneous sensor network environment. The main objective is to provide a solution based on Wireless and Multimedia Sensor Networks (W&MSN) for monitoring and tracking of object (person/vehicle) in secured area. The multi-tier, heterogeneous sensor network adapted for efficient usage of image data. The object detection is carried out with background subtraction technique. The detected blob region is taken as input for extracting the features based on Haar wavelet. The feature extraction is followed by joint boosting algorithm to classify as interested object or not. The object detection is combined with Kalman Filter to accurately track the movement of desired objects in the given area. This approach provides better detection and tracking of person even in the presence of occlusion and multiple persons in the environment.
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References
Torralba, A., Murphy, K.P., Freeman, W.T.: Sharing visual features for multiclass and multiview object detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(5), 854–869 (2007)
Viola, P., Jones, M.: Robust real-time object detection. International Journal of Computer Vision 57(2), 137–154 (2004)
Comaniciu, D., Ramesh, V., Meer, P.: Kernel-based object tracking. IEEE Transaction Pattern Analysis Machine Intelligence 25(5), 564–575 (2003)
Akyildiz, I.F., Melodia, T., Chowdhury, K.R.: A Survey On Wireless Multimedia Sensor Networks. Computer Network 51, 921–960 (2007)
He, T., Krishnamurthy, S., Luo, L., Yan, T., Krogh, B., Gu, L., Stoleru, R., Zhou, G., Cao, Q., Vicaire, P., Stankovic, J.A., Abdelzaher, T.F., Hui, J.: Vigilnet: An Integrated Sensor Network System For Energy-Efficient Surveillance. ACM Transaction on Sensor Networks (TOSN) 2, 1–38 (2006)
Papageorgiou, C., Poggio, T.: A Trainable System for Object Detection. International Journal of Computer Vision 38(1), 15–33 (2000)
Madzarov, G., Gjorgjevikj, D., Chaorbev, I.: A Multi-class SVM Classifier Utilizing Binary Decision Tree. Journal of Informatica 33, 233–241 (2009)
Rabiner, L.R., Huang, B.H.: An Introduction to Hidden Markov Models. IEEE ASSP Magazine, 4–16 (January 1986)
Kang, J., Cohen, I., Medioni, G.: Soccer player tracking across uncalibrated camera streams. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (October 2003)
Zhao, T., Nevatia, R., Lv, F.: Segmentation and tracking of multiple humans in complex situations. In: 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), December 8-14, IEEE Computer Society, Kauai (2001)
Piater, J.H., Crowley, J.L.: Multi-modal tracking of interacting targets using Gaussian approximations. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (December 2001)
Rabiner, L.: A tutorial on hidden markov models and selected applications in speech recognition. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, vol. 77
Rigoll, G., Eickeler, S., Müller, S.: Person Trackin. In: Real-World Scenarios Using Statistical Method. In: IEEE Fourth International Conference on Automatic Face and Gesture Recognition (August 2002)
Welch, G., Bishop, G.: An Introduction to the Kalman Filter. University Of North Carolina At Chapel Hill (2001)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), San Diego, CA, USA, vol. 1, pp. 886–893 (2005)
Bhargavi, R., Sri Ganesh, K., RajaSekar, M., Rabinder Singh, P., Vaidehi, V.: An Integrated System of Complex Event Processing and Kalman Filter for Multiple People Tracking in WSN. In: proceedings of International Conference on Recent Trends in Information Technology (ICRTIT), June 3-5, pp. 890–895. MIT, Anna University (2011)
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Vasuhi, S., Annis Fathima, A., Anand Shanmugam, S., Vaidehi, V. (2012). Object Detection and Tracking in Secured Area with Wireless and Multimedia Sensor Network. In: Benlamri, R. (eds) Networked Digital Technologies. NDT 2012. Communications in Computer and Information Science, vol 294. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30567-2_30
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DOI: https://doi.org/10.1007/978-3-642-30567-2_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30566-5
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