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Coopetitive visual surveillance using model predictive control

Published: 11 November 2005 Publication History

Abstract

Active cooperative sensing with multiple sensors is being actively researched in visual surveillance. However, active cooperative sensing often suffers from the delay in information exchange among the sensors and also from sensor reaction delays. This is because simplistic control strategies like Proportional Integral Differential (PID), that do not employ the look-ahead strategy, often fail to counterbalance these delays at real time. Hence, there is a need for more sophisticated interaction and control mechanisms that can overcome the delay problems. In this paper, we propose a coopetitive framework using Model Predictive Control (MPC) which allows the sensors to not only 'compete' as well as 'cooperate' with each other to perform the designated task in the best possible manner but also to dynamically swap their roles and sub-goals rather than just the parameters. MPC is used as a feedback control mechanism to allow sensors to react not only based on past observations but also on possible future events. We demonstrate the utility of our framework in a dual camera surveillance setup with the goal of capturing the high resolution images of intruders in the surveyed rectangular area e.g. an ATM lobby or a museum. The results are promising and clearly establish the efficacy of coopetition as an effective form of interaction between sensors and MPC as a superior feedback mechanism than the PID.

References

[1]
J. P. Barreto, J. Batista, P. Peixoto, and H. Araujo. Integrating vision and control to achieve high perfomance active tracking. Technical report, TR-BAR-0202, ISR/DEEC - University of Coimbra, Febraury 2002.
[2]
R. Collins, A. Lipton, H. Fujiyoshi, and T. Kanade. Algorithms for cooperative multi-sensor surveillance. In Proceedings of the IEEE, pages 1456--1477, October 2001.
[3]
R. Collins, A. Lipton, T. Kanade, H. Fujiyoshi, D. Duggins, Y. Tsin, D. Tolliver, N. Enomoto, and O. Hasegawa. A system for video surveillance and monitoring. Technical report, CMU-RI-TR-00-12, Robotics Institute, CMU, USA, May 2000.
[4]
Datasets. In IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, Breckenridge, USA, January 2005.
[5]
M. Dias and A. Stentz. A market approach to multirobot coordination. Technical report, CMU-RI-TR-01-26 - Carnegie Mellon University, August 2001.
[6]
M. Greiffenhagen, V. Ramesh, and D. Comaniciu. Statistical modeling and performance characterization of a real-time dual camera surveillance system. In Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Hilton Head Island, USA, June 2000.
[7]
M. Khadir and J. Ringwood. Linear and nonlinear model predictive control design for a milk pasteurization plant. Journal of Control and Intelligent Systems, 31(1), 2003.
[8]
K.-Y. Lam and C. K. H. Chiu. Adaptive visual object surveillance with continuously moving panning camera. In Proceedings of the 2nd ACM International Workshop on Video surveillance and Sensor Networks, October 2004.
[9]
Q. Liu, D. Kimber, J. Foote, L. Wilcox, and J. Boreczky. FLYSPEC: A multi-user video camera system with hybrid human and automatic control. In ACM International Conference on Multimedia, New York, USA, December 2002.
[10]
M. Morari, J. H. Lee, C. E. Garcia, and D. M. Prett. Model Predictive Control. Prentice Hall, Englewood Cliffs, New Jersey, 2003.
[11]
N. Papanikolopoulos, P. Khosla, and T. Kanade. Visual tracking of a moving target by a camera mounted on a robot: A combination of control and vision. IEEE Transactions on Robotics and Automation, 9(1), 1993.
[12]
P. K. Roy, G. Mann, B. C. Hawlader, V. Masek, and S. O. Young. Comparative study of model predictive and decoupled PID controller for a multivariable soil heating process. In The 14th Annual IEEE Newfoundland Electrical and Computer Engineering Conference, Newfoundland, Canada, October 2004.
[13]
M. Saedan and M. H. A. Jr. 3D vision-based control on an industrial robot. In Proceedings of IASTED International Conference on Robotics and Applications, Clearwater, USA, November 2001.
[14]
P. Sharkey and D. Murray. Delays versus performance of visually guided systems. In IEE Proceedings on Control Theory Applications, pages 436--447, September 1996.
[15]
S. Swarup, T. Oezer, S. R. Ray, and T. J. Anastasio. A self-aiming camera based on neurophysical principless. In Proceedings of The International Joint Conference on Neural Networks, Portland, USA, July 2003.
[16]
J. Wang, C. Zhang, and H. Shum. Face image resolution versus face recognition performance based on two global methods. In Asian Conference on Computer Vision, Jeju Island, Korea, January 2004.
[17]
X. Zhou, R. Collins, T. Kanade, and P. Metes. A master-slave system to acquire biometric imagery of humans at distance. In ACM International Workshop on Video Surveillance, Berkley, USA, November 2003.

Cited By

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  • (2019)Coopetition as an Emerging Trend in Research: Perspectives for Safety & SecuritySafety10.3390/safety50300615:3(61)Online publication date: 1-Sep-2019
  • (2015)Large-Area, Multilayered, and High-Resolution Visual Monitoring Using a Dual-Camera SystemACM Transactions on Multimedia Computing, Communications, and Applications10.1145/264586211:2(1-23)Online publication date: 7-Jan-2015
  • (2010)Automatic path modeling by image processing techniques2010 International Conference on Machine Learning and Cybernetics10.1109/ICMLC.2010.5580872(2589-2594)Online publication date: Jul-2010
  • Show More Cited By

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cover image ACM Conferences
VSSN '05: Proceedings of the third ACM international workshop on Video surveillance & sensor networks
November 2005
168 pages
ISBN:1595932429
DOI:10.1145/1099396
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 11 November 2005

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Author Tags

  1. coopetition
  2. model predictive control
  3. video surveillance

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MM&Sec '05
MM&Sec '05: Multimedia and Security Workshop 2005
November 11, 2005
Hilton, Singapore

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Cited By

View all
  • (2019)Coopetition as an Emerging Trend in Research: Perspectives for Safety & SecuritySafety10.3390/safety50300615:3(61)Online publication date: 1-Sep-2019
  • (2015)Large-Area, Multilayered, and High-Resolution Visual Monitoring Using a Dual-Camera SystemACM Transactions on Multimedia Computing, Communications, and Applications10.1145/264586211:2(1-23)Online publication date: 7-Jan-2015
  • (2010)Automatic path modeling by image processing techniques2010 International Conference on Machine Learning and Cybernetics10.1109/ICMLC.2010.5580872(2589-2594)Online publication date: Jul-2010
  • (2008)Robust object tracking with background-weighted local kernelsComputer Vision and Image Understanding10.1016/j.cviu.2008.05.005112:3(296-309)Online publication date: 1-Dec-2008
  • (2008)Coopetitive multi-camera surveillance using model predictive controlMachine Vision and Applications10.1007/s00138-007-0082-219:5-6(375-393)Online publication date: 1-Oct-2008
  • (2007)Coopetitive multimedia surveillanceProceedings of the 13th International conference on Multimedia Modeling - Volume Part II10.1007/978-3-540-69429-8_35(343-352)Online publication date: 9-Jan-2007

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