ABSTRACT
This paper describes an application that enables quick reconstruction of interconnected events, sparsely captured by one or more surveillance cameras. Unlike related efforts, our approach does not require indexing, advance knowledge of potential search criteria, nor a solution to the generalized object-recognition problem. Instead, we strategically pair the intelligence and skill of a human investigator with the speed and flexibility of a parallel image search engine that exploits local storage and processing capabilities distributed across large collections of video recording devices. The result is a system for fast, interactive, brute-force video searching which is both effective and highly scalable.
- A. Acharya, M. Uysal, and J. Saltz. Active disks: Programming model, algorithms and evaluation. In Proceedings of ASPLOS, 1998. Google ScholarDigital Library
- C. Carson, S. Belongie, H. Greenspan, and J. Malik. Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(8), 2002. Google ScholarDigital Library
- R. Collins, A. Lipton, and T. Kanade. A system for video surveillance and monitoring. In Proceedings of the American Nuclear Society (ANS) Eighth International Topical Meeting on Robotics and Remote Systems, 1999.Google Scholar
- C. Faloutsos, R. Barber, M. Flickner, J. Hafner, W. Niblack, D. Petkovic, and W. Equitz. Efficient and effective querying by image content. Journal of Intelligent Information Systems, 3(3/4), 1994. Google ScholarDigital Library
- M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker. Query by image and video content: the QBIC system. IEEE Computer, 28, 1995. Google ScholarDigital Library
- D. Forsyth and J. Ponce. Computer vision: a modern approach. Prentice Hall, 2002. Google ScholarDigital Library
- W. Grimson, C. Stauffer, R. Romano, and L. Lee. Using adaptive tracking to classify and monitor activities in a site. In Proceedings of IEEE Computer Vision and Pattern Recognition,1998. Google ScholarDigital Library
- J. Hellerstein, R. Avnur, A. Chou, C. Hidber, V. Raman, T. Roth, and P. Haas. Interactive data analysis: The CONTROL project. IEEE Computer, August 1999. Google ScholarDigital Library
- J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister. System architecture directions for networked sensors. In Architectural Support for Programming Languages and Operating Systems, pages 93--104, 2000. Google ScholarDigital Library
- L. Huston, R. Sukthankar, R. Wickremesinghe, M. Satyanarayanan, G. R. Ganger, E. Riedel, and A. Ailamaki. Diamond: A storage architecture for early discard in interactive search. In Proceedings of USENIX Conference on File and Storage Technologies (FAST), 2004. Google ScholarDigital Library
- K. Keeton, D. Patterson, and J. Hellerstein. A case for intelligent disks (IDISKs). SIGMOD Record, 27(3), 1998. Google ScholarDigital Library
- R. Min, M. Bhardwaj, S. Cho, A. Sinha, E. Shih, A. Wang, and A.Chandrakasan. Low-power wireless sensor networks. Proceedings of VLSI Design, 2001. Google ScholarDigital Library
- S. Nath, A. Deshpande, Y. Ke, P. Gibbons, B. Karp, and S. Seshan. Irisnet: An architecture for internet-scale sensing services. In Proceedings of VLDB, 2003. Google ScholarDigital Library
- P. Pillai, Y. Ke, and J. Campbell. Multi-fidelity storage. In Proceedings of ACM Workshop on Visual Surveillance and Sensor Networks, 2004. Google ScholarDigital Library
- E. Riedel, G. Gibson, and C. Faloutsos. Active storage for large-scale data mining and multimedia. In Proceedings of VLDB, August 1998. Google ScholarDigital Library
- H. Rowley, S. Baluja, and T. Kanade. Neural network-based face detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(1), 1998. Google ScholarDigital Library
- Y. Rubner, C. Tomasi, and L. J. Guibas. The earth mover's distance as a metric for image retrieval. International Journal of Computer Vision, 40(2), 2000. Google ScholarDigital Library
- H. Schneiderman and T. Kanade. A statistical model for 3D object detection applied to faces and cars. In Proceedings of IEEE Computer Vision and Pattern Recognition, 2000.Google ScholarCross Ref
- M. Swain and B. Ballard. Color indexing. International Journal of Computer Vision, 7, 1991. Google ScholarDigital Library
- P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proceedings of IEEE Computer Vision and Pattern Recognition, 2001.Google ScholarCross Ref
Index Terms
- Forensic video reconstruction
Recommendations
Interactive Search vs. Automatic Search: An Extensive Study on Video Retrieval
This article conducts user evaluation to study the performance difference between interactive and automatic search. Particularly, the study aims to provide empirical insights of how the performance landscape of video search changes, with tens of ...
Reducing Click and Skip Errors in Search Result Ranking
WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data MiningSearch engines provide result summaries to help users quickly identify whether or not it is worthwhile to click on a result and read in detail. However, users may visit non-relevant results and/or skip relevant ones. These actions are usually harmful to ...
Balancing thread based navigation for targeted video search
CIVR '08: Proceedings of the 2008 international conference on Content-based image and video retrievalVarious query methods for video search exist. Because of the semantic gap each method has its limitations. We argue that for effective retrieval query methods need to be combined at retrieval time. However, switching query methods often involves a ...
Comments