Difference between revisions of "SCN"
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== Software ==
== Software ==
Revision as of 21:58, 13 July 2012
Smart camera networks (SCNs) merge computer vision, distributed processing, and sensor network disciplines to solve problems in multi-camera applications by providing valuable information through distributed sensing and collaborative in-network processing. Collaboration in sensor networks is necessary not only to compensate for the processing, sensing, energy, and bandwidth limitations of each sensor node but also to improve the accuracy and robustness of the network. Collaborative processing in SCNs is more challenging than in conventional scalar sensor networks (SSNs) because of three unique features of cameras, including the extremely higher data rate, the directional sensing characteristics with limited field of view (FOV), and the existence of visual occlusion. An integrated research is carried out to tackle the unique challenges presented by SCNs where collaboration is the key. Three aspects of collaborative processing are investigated, 1) coverage estimation‚ in the presence of visual occlusions to provide adequate redundancy in sensing coverage to enable collaboration where the statistics of visual coverage blends the statistics of camera nodes and targets, 2) clustering‚ to schedule an efficient sleep-wakeup pattern among neighbor nodes formed by image comparison-based semantic neighbor selection algorithm for more efficient collaboration, and 3) distributed optimization‚ for in-network data processing that concerns how to effectively obtain robust and accurate integration results from multiple distributed sensors for challenging vision tasks like target detection, localization, and tracking in crowds.
- NSF CNS-1017156
- Jiajia Luo, Ph.D. Candidate, Started Fall 2009
- Kefa Lu, Ph.D. Candidate, Started Fall 2010
- Zhibo Wang, Ph.D. Candidate, Started Spring 2011
- Mahmut Karakaya, Collaborative Solutions to Visual Sensor Networks, Ph.D., Summer 2011
- Yang Bai, Feature-based Image Comparison and Its Application in Wireless Visual Sensor Networks, Ph.D., Spring 2011
- Cheng Qian, A Distributed Solution for Visual Sensor Networks to Detect Targets in Crowds, M.S., Summer 2006
- Chris Beall, Distributed Self-Deployment in Visual Sensor Networks, M.S., Summer 2006
- Clay Taylor, Undergraduate Student
- M. Karakaya, H. Qi, "Coverage estimation for crowded targets in visual sensor networks," ACM Transactions on Sensor Networks, 8(3), July 2012.
- Y. Bai, H. Qi, "Feature-based image comparison for semantic neighbor selection in resource-constrained visual sensor networks," Eurasip Journal on Image and Video Processing (IVP), vol. 2010, Article ID 469563, 11 pages, 2010. doi: 10.1155/2010/469563.
- M. Karakaya, H. Qi, "Distributed target localization using a progressive certainty map in visual sensor networks ," Ad Hoc Networks, In Press, ISSN 1570-8705, DOI: 10.1016/j.adhoc.2010.08.006. (http://www.sciencedirect.com/science/article/B7576-50RP221-6/2/60af0fa0415bcbd602d526d6d1a21c70), August 2010.
- M. Karakaya, H. Qi, "Coverage estimation in heterogeneous visual sensor networks," IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), pages 41-49, Hangzhou, China, May 16-18, 2012.
- Z. Wang, C. Taylor, Q. Cao, H. Qi, Z. Wang, "Demo abstract: Friendbook: Privacy-preserving friend matching based on shared interests," The 9th ACM Conference on Embedded Networked Sensor Systems (SenSys), pages 397-398, Seattle, WA, November 1-4, 2011.
- M. Karakaya, H. Qi, "Detection-based tracking for crowded targets in distributed visual sensor networks," 2nd International Workshop on Future of Instrumentation, Oak Ridge, November 2011.
- X. Ma, S. Djouadi, Q. Cao, "LIPS: Link prediction as a service for adaptive data aggregation in wireless sensor networks," IEEE International Conference on Distributed Computing in Sensor Networks (DCOSS), Barcelona, Spain, June 27-29, 2011.
- Q. Cao, X. Wang, H. Qi, T. He, "r-Kernel: An operating system foundation for highly reliable networked embedded systems," The 30th International Conference on Computer Communications (INFOCOM), Shanghai, China, April 10-15, 2011.
- M. Karakaya, H.Qi, "Fault Detection, Correction, and Tolerance for Collaborative Target Localization in Visual Sensor Networks" 4th ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), Atlanta, GA, Aug 30-Sep 2, 2010.
- J. Luo, H. Qi, "Distributed object recognition via feature unmixing," ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), 8 pages, Atlanta, GA, August 31 - September 4, 2010.
- M. Karakaya, H.Qi, "Target Detection and Counting using a Progressive Certainty Map in Distributed Visual Sensor Networks" 3rd ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), Como, Italy, Aug 30-Sep 2, 2009. (Best Paper Award)
- Y. Bai, H. Qi, "Redundancy removal through semantic neighbor selection in visual sensor networks," Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), 8 pages, Como, Italy, August 30 - September 2, 2009.
- C. Qian, H. Qi, "A distributed solution to detect targets in crowds using visual sensor networks" 2nd ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), Stanford University, CA, September 7-11, 2008.
- C. Qian, H. Qi, "Coverage estimation in the presence of occlusions for visual sensor networks," International Conference on Distributed Computing in Sensor Systems (DCOSS), Santorini Island, Greece, June 11-14, 2008.
- C. Beall, H. Qi, "Distributed self-deployment in visual sensor networks" Ninth International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore, December 5-8, 2006.