Title | ||
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A Dempster-Shafer Theory And Uninorm-Based Framework Of Reasoning And Multiattribute Decision-Making For Surveillance System |
Abstract | ||
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Closed-circuit television and sensor-based intelligent surveillance systems have attracted considerable attentions in the field of public security affairs. To provide real-time reaction in the case of a huge volume of the surveillance data, researchers have proposed event-reasoning frameworks for modeling and inferring events of interest. However, they do not support decision-making, which is very important for surveillance operators. To this end, this paper incorporate a function of decision-making in an event-reasoning framework, so that our model not only can perform event-reasoning but also can predict, rank, and alarm threats according to uncertain information from multiple heterogeneous sources. In particular, we propose a multiattribute decision-making model, in which an object being watched is modeled as a multiattribute event, where each attribute corresponds to a specific source, and the information from each source can be used to elicit a local threat degree of different malicious situations with respect to the corresponding attribute. Moreover, to assess an overall threat degree of an object being observed, we also propose a method to fuse the conflict threat degrees regarding all the relevant attributes. Finally, we demonstrate the effectiveness of our framework by an airport security surveillance scenario. |
Year | DOI | Venue |
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2019 | 10.1002/int.22175 | INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS |
Keywords | Field | DocType |
ambiguity, decision-making under uncertainty, D-S theory of evidence, event modeling and reasoning, multiattribute decision-making, surveillance systems, uninorm | Artificial intelligence,Dempster–Shafer theory,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
34 | 11 | 0884-8173 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Wenjun Ma | 1 | 81 | 9.51 |
Weiru Liu | 2 | 1597 | 112.05 |
Xudong Luo | 3 | 773 | 64.70 |
Kevin McAreavey | 4 | 23 | 8.16 |
Yuncheng Jiang | 5 | 375 | 24.36 |
Jianbing Ma | 6 | 242 | 15.73 |