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In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.
|Title of host publication||Knowledge Science, Engineering and Management - The 8th International Conference on Knowledge Science, Engineering and Management (KSEM15).|
|Editors||Songmao Zhang, Martin Wirsing, Zilil Zang|
|Number of pages||12|
|Publication status||Published - 01 Nov 2015|
|Event||The 8th International Conference on Knowledge Science, Engineering and Management (KSEM15). - ChengDu, China|
Duration: 29 Oct 2015 → 31 Oct 2015
|Name||Lecture Notes in Artificial Intelligence|
|Conference||The 8th International Conference on Knowledge Science, Engineering and Management (KSEM15).|
|Period||29/10/2015 → 31/10/2015|
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