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Advances in Multimedia
Volume 2012 (2012), Article ID 639649, 14 pages
Adaptive Transformation for Robust Privacy Protection in Video Surveillance
1School of Computing, National University of Singapore, Singapore 117417
2Department of Applied Computer Science, The University of Winnipeg, MB, Canada R3T 5V9
3Information and Computer Science Department, University of California, Irvine, CA 92697-3425, USA
Received 30 November 2011; Revised 6 February 2012; Accepted 6 February 2012
Academic Editor: Martin Reisslein
Copyright © 2012 Mukesh Saini et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- M. Boyle, C. Edwards, and S. Greenberg, “The effects of filtered video on awareness and privacy,” in Proceedings of the ACM Conference on Computer Supported Cooperative Work, pp. 1–10, December 2000.
- M. Saini, P. K. Atrey, S. Mehrotra, S. Emmanuel, and M. Kankanhalli, “Privacy modeling for video data publication,” in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME '10), pp. 60–65, July 2010.
- A. Senior, S. Pankanti, A. Hampapur et al., “Enabling video privacy through computer vision,” IEEE Security and Privacy, vol. 3, no. 3, pp. 50–57, 2005.
- D. A. Fidaleo, H. A. Nguyen, and M. Trivedi, “The networked sensor tapestry (nest): a privacy enhanced software architecture for interactive analysis of data in video-sensor networks,” in Proceedings of the 2nd ACM International Workshop on Video Sureveillance and Sensor Networks (VSSN '04), pp. 46–53, 2004.
- J. Wickramasuriya, M. Datt, S. Mehrotra, and N. Venkatasubramanian, “Privacy protecting data collection in media spaces,” in Proceedings of the 12th ACM International Conference on Multimedia, pp. 48–55, usa, October 2004.
- T. Koshimizu, T. Toriyama, and N. Babaguchi, “Factors on the sense of privacy in video surveillance,” in Proceedings of the 3rd ACM Workshop on Continuous Archival and Retrievalof Personal Experiences (CARPE '06), pp. 35–43, 2006.
- B. Thuraisingham, G. Lavee, E. Bertino, J. Fan, and L. Khan, “Access control, confidentiality and privacy for video surveillance databases,” in Proceedings of the 11th ACM Symposium on Access Control Models and Technologies (SACMAT '06), pp. 1–10, June 2006.
- P. Carrillo, H. Kalva, and S. Magliveras, “Compression independent object encryption for ensuring privacy in video surveillance,” in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME '08), pp. 273–276, June 2008.
- J. K. Paruchuri, S. C. S. Cheung, and M. W. Hail, “Video data hiding for managing privacy information in surveillance systems,” Eurasip Journal on Information Security, vol. 2009, Article ID 236139, 7 pages, 2009.
- F. Z. Qureshi, “Object-video streams for preserving privacy in video surveillance,” in Proceedings of the 6th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS '09), pp. 442–447, 2009.
- S. Moncrieff, S. Venkatesh, and G. West, “Dynamic privacy assessment in a smart house environment using multimodal sensing,” ACM Transactions on Multimedia Computing, Communications and Applications, vol. 5, no. 2, pp. 1–29, 2008.
- T. Spindler, C. Wartmann, and L. Hovestadt, “Privacy in video surveilled areas,” in Proceedings of the ACM International Conference on Privacy, Security and Trust, pp. 1–10, 2006.
- A. Elgammal, R. Duraiswami, D. Harwood, and L. S. Davis, “Background and foreground modeling using nonparametric kernel density estimation for visual surveillance,” Proceedings of the IEEE, vol. 90, no. 7, pp. 1151–1163, 2002.
- H. Kruegle, CCTV Surveillance: Analog and Digital Video Practices and Technology, Butterworth-Heinemann, Boston, Mass, USA, 2006.
- R. Kasturi, D. Goldgof, P. Soundararajan et al., “Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 2, pp. 319–336, 2009.
- E. Hjelmås and B. K. Low, “Face detection: a survey,” Computer Vision and Image Understanding, vol. 83, no. 3, pp. 236–274, 2001.
- Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, 2004.
- S. Chikkerur, V. Sundaram, M. Reisslein, and L. J. Karam, “Objective video quality assessment methods: a classification, review, and performance comparison,” IEEE Transactions on Broadcasting, vol. 57, no. 2, pp. 165–182, 2011.
- K. Seshadrinathan, R. Soundararajan, A. C. Bovik, and L. K. Cormack, “Study of subjective and objective quality assessment of video,” IEEE Transactions on Image Processing, vol. 19, no. 6, Article ID 5404314, pp. 1427–1441, 2010.
- PETS, “Performance evaluation of tracking and surveillance,” 2000-2011, http://www.cvg.cs.rdg.ac.uk/slides/pets.html.
- C. Stauffer and W. E. L. Grimson, “Adaptive background mixture models for real-time tracking,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '99), vol. 2, pp. 246–252, June 1999.