Print Email Facebook Twitter Reasoning about threats: From observables to situation assessment Title Reasoning about threats: From observables to situation assessment Author Burghouts, G.J. Marck, J.W. Publication year 2011 Abstract We propose a mechanism to assess threats that are based on observables. Observables are properties of persons, i.e., their behavior and interaction with other persons and objects. We consider observables that can be extracted from sensor signals and intelligence. In this paper, we discuss situation assessment that is based on observables for threat assessment. In the experiments, the assessment is evaluated for scenarios that are relevant to antiterrorism and crowd control. The experiments are performed within an evaluation framework, where the setup is such that conclusions can be drawn concerning: 1) the accuracy and robustness of an architecture to assess situations with respect to threats; and 2) the architectures dependence of the underlying observables in terms of their false positive and negative rates. One of the interesting conclusions is that discriminative assessment of threatening situations can be achieved by combining generic observables. Situations can be assessed with a precision of 90 at a false positive and negative rate of 15 using only eight learning examples. In a real-world experiment at a large train station, we have classified various types of crowd dynamics. Using simple video features of shape and motion, we have proposed a scheme to translate such features into observables that can be classified by a conditional random field (CRF). The implemented CRF shows to classify successfully the crowd dynamics up to 80 % accuracy. © 2010 IEEE. Subject Physics & ElectronicsII - Intelligent ImagingTS - Technical SciencesImage processingArchitectureevaluation frameworkinformation processingobservablessituation understandingthreat recognitionConditional random fieldCrowd controlCrowd dynamicsEvaluation frameworkFalse positiveNegative ratesobservablesReal world experimentSensor signalsSituation assessmentSituation understandingThreat assessmentthreat recognitionTrain stationsVideo featuresArchitectureData processingExperimentsPattern recognitionTerrorismRating To reference this document use: http://resolver.tudelft.nl/uuid:4b8755a7-ce14-43f8-bd8b-198644479d6a DOI https://doi.org/10.1109/tsmcc.2011.2135344 TNO identifier 436018 ISSN 1094-6977 Source IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 41 (5), 608-616 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.