A Dempster-Shafer theory and uninorm-based framework of reasoning and multiattribute decision-making for surveillance system
| Autor: | Yuncheng Jiang, Kevin McAreavey, Wenjun Ma, Xudong Luo, Jianbing Ma, Weiru Liu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
D-S theory of evidence
surveillance systems decision-making under uncertainty event modeling and reasoning Computer science business.industry media_common.quotation_subject Ambiguity Theoretical Computer Science Human-Computer Interaction Artificial Intelligence Dempster–Shafer theory ambiguity uninorm Artificial intelligence business multiattribute decision-making Software media_common |
| Zdroj: | Ma, W, Liu, W, Luo, X, McAreavey, K, Jiang, Y & Ma, J 2019, ' A Dempster-Shafer theory and uninorm-based framework of reasoning and multiattribute decision-making for surveillance system ', International Journal of Intelligent Systems, vol. 34, no. 11, pp. 3077-3104 . https://doi.org/10.1002/int.22175 |
| DOI: | 10.1002/int.22175 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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