Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2012.6466788
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dc.titleWide area video surveillance with spatial-temporal constraints
dc.contributor.authorShu H.
dc.contributor.authorHsu Y.-F.
dc.contributor.authorYu S.-S.
dc.contributor.authorChen T.
dc.date.accessioned2018-08-21T04:57:23Z
dc.date.available2018-08-21T04:57:23Z
dc.date.issued2012
dc.identifier.citationShu H., Hsu Y.-F., Yu S.-S., Chen T. (2012). Wide area video surveillance with spatial-temporal constraints. Proceedings - International Conference on Image Processing, ICIP : 33-36. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2012.6466788
dc.identifier.isbn9781467325332
dc.identifier.issn15224880
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/146122
dc.description.abstractWe propose a novel method for the problem of target retrieval for wide area video surveillance (WAVS). Different from previous methods, our algorithm does not require environment model construction nor the learning or usage of any transition probabilities. Furthermore, our method can be applied to an arbitrarily large area for surveillance. The essence of our method lies in an optimization problem formulation using only the shortest driving distance between pairs of cameras, and the provision of an algorithm that finds a global optimum to the optimization. Experiments show that our method can achieve 99% precision and > 80% recall on an input of thousands of frames, which far exceeds the performance of the baseline, whilst taking under 10 seconds to run on a 1.67GHz Intel Centrino laptop. This makes it feasibly deployable on handheld devices in a police car.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentOFFICE OF THE PROVOST
dc.contributor.departmentDEPT OF COMPUTER SCIENCE
dc.description.doi10.1109/ICIP.2012.6466788
dc.description.sourcetitleProceedings - International Conference on Image Processing, ICIP
dc.description.page33-36
dc.published.statepublished
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