Abstract
Multimedia surveillance systems utilize multiple correlated media streams, each of which has a different confidence level in accomplishing various surveillance tasks. For example, the system designer may have a higher confidence in the video stream compared to the audio stream for detecting humans running events. The confidence level of streams is usually precomputed based on their past accuracy. This traditional approach is cumbersome especially when we add a new stream in the system without the knowledge of its past history. This paper proposes a novel method which dynamically computes the confidence level of new streams based on their agreement/disagreement with the already trusted streams. The preliminary experimental results show the utility of our method.
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
Preview
Unable to display preview. Download preview PDF.
References
Atrey, P.K., Maddage, N.C., Kankanhalli, M.S.: Audio based event detection for multimedia surveillance. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. V813–816 (2006)
Rama, K.G.S., Atrey, P.K., Singh, V.K., Ramakrishnan, K., Kankanhalli, M.S.: A design methodology for selection and placement of sensors in multimedia surveillance systems. In: The 4th ACM International Workshop on Video Surveillance and Sensor Networks, Santa Barbara, CA, USA ( (2006)
Prati, A., Vezzani, R., Benini, L., Farella, E., Zappi, P.: An integrated multi-modal sensor network for video surveillance. In: The ACM International Workshop on Video Surveillance and Sensor Networks, Singapore, pp. 95–102 (2005)
Atrey, P.K., Kankanhalli, M.S., Jain, R.: A framework for information assimilation in multimedia surveillance systems. ACM Multimedia Systems Journal (2006)
Tatbul, N., Buller, M., Hoyt, R., Mullen, S., Zdonik, S.: Confidence-based data management for personal area sensor networks. In: The Workshop on Data Management for Sensor Networks, pp. 24–31 (2004)
Tavakoli, A., Zhang, J., Son, S.H.: Group-based event detection in undersea sensor networks. In: Second International Workshop on Networked Sensing Systems, San Diego, California, USA (2005)
Ioannou, S., Wallace, M., Karpouzis, K., Raouzaiou, A., Kollias, S.: Confidence-based fusion of multiple feature cues for facial expresssion recognition. In: The 14th IEEE International Conference on Fuzzy Systems, Reno, Nevada, USA, pp. 207–212 (2005)
Siegel, M., Wu, H.: Confidence fusion. In: IEEE International Workshop on Robot Sensing, pp. 96–99 (2004)
Conaire, C.O., Connor, N.O., Cooke, E., Smeaton, A.: Detection thresholding using mutual information. In: International Conference on Computer Vision Theory and Applications, Setubal, Portugal (2006)
Jain, A.K., Murty, M.N., Flynn, P.J.: Data clustering: A review. ACM Computing Surveys 31(3), 264–323 (1999)
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Ft. Collins, CO, USA, vol. 2, pp. 252–258 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Atrey, P.K., Kankanhalli, M.S., El Saddik, A. (2006). Confidence Building Among Correlated Streams in Multimedia Surveillance Systems. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69429-8_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-69429-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69428-1
Online ISBN: 978-3-540-69429-8
eBook Packages: Computer ScienceComputer Science (R0)