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Dragos Datcu, & Leon J.M. Rothkrantz. (2007). The use of active appearance model for facial expression recognition in crisis environments. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 515–524). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In the past a crisis event was notified by local witnesses that use to make phone calls to the special services. They reported by speech according to their observation on the crisis site. The recent improvements in the area of human computer interfaces make possible the development of context-aware systems for crisis management that support people in escaping a crisis even before external help is available at site. Apart from collecting the people's reports on the crisis, these systems are assumed to automatically extract useful clues during typical human computer interaction sessions. The novelty of the current research resides in the attempt to involve computer vision techniques for performing an automatic evaluation of facial expressions during human-computer interaction sessions with a crisis management system. The current paper details an approach for an automatic facial expression recognition module that may be included in crisis-oriented applications. The algorithm uses Active Appearance Model for facial shape extraction and SVM classifier for Action Units detection and facial expression recognition.
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Julie Dugdale, Bernard Pavard, Nico Pallamin, Mehdi El Jed, & Laurent Maugan. (2004). Emergency fire incident training in a virtual world. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 167–172). Brussels: Royal Flemish Academy of Belgium.
Abstract: The effectiveness of 'close to reality' training simulations is due to the fact that they provide a sense of immersion and allow several participants to interact naturally. However, they are expensive, time-consuming, difficult to organise and have a limited scope. We present a virtual reality training simulator which overcomes these disadvantages. We describe the approach and methodology and conclude with a discussion of the most crucial challenges when developing such a system. In this paper we would like to introduce the notion of cultural technologies which produce a sense of social as well as cultural immersion. We will discuss the main ingredients of such an immersion, in particular the notion of situated virtual interaction (how interactions in a virtual world can be comparable with human interactions in real situations). We also discuss on the role of interfaces (real time motion capture) and emotional expression in the design of such environments. © Proceedings ISCRAM 2004.
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Siska Fitrianie, Ronald Poppe, Trung H. Bui, Alin Gavril Chitu, Dragos Datcu, Ramón Dor, et al. (2007). A multimodal human-computer interaction framework for research into crisis management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 149–158). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Unreliable communication networks, chaotic environments and stressful conditions can make communication during crisis events difficult. The current practice in crisis management can be improved by introducing ICT systems in the process. However, much experimentation is needed to determine where and how ICT can aid. Therefore, we propose a framework in which predefined modules can be connected in an ad hoc fashion. Such a framework allows for rapid development and evaluation of such ICT systems. The framework offers recognition of various communication modalities including speech, lip movement, facial expression, handwriting and drawing, body gesture, text and visual symbols. It provides mechanisms to fuse these modalities into a context dependent interpretation of the current situation and generate appropriate the multimodal information responses. The proposed toolbox can be used as part of a disaster and rescue simulation. We propose evaluation methods, and focus on the technological aspects of our framework.
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Stephen C. Fortier, & Ioannis M. Dokas. (2008). Setting the specification framework of an Early Warning System using IDEF0 and information modeling. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 441–450). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Our goal is to develop an Early Warning System for an engineering system with a special interest in applying this to a material recovery facility. This on-going research points out that there is no clear definition of what Early Warning Systems are. A literature search for Early Warning Systems identifies hundred of thousands hits (Buchanan-Smith, 1999; Davies, Buchanan-Smith, Lambert, 1991). Almost all of the references had to do with financial systems for third world countries, tracking the destructive nature of violent conflicts that led to human suffering, or systems for syndromic surveillance. The goal of our research, and of this paper, is to define a framework for creating a specification that can be considered as the basis for the development of any Early Warning System-specifically for engineering systems. Therefore, we will describe Early Warning Systems and its requirements and specifications. Based on specification patterns, we have developed an abstract model of an Early Warning System; and developed an IDEF0 model of a material recovery facility that provides the framework for specifying an Early Warning System. The Early Warning System is then specified using information modeling.
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Takuya Oki. (2018). Possibility of Using Tweets to Detect Crowd Congestion: A Case Study Using Tweets just before/after the Great East Japan Earthquake. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 584–596). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: During large earthquakes, it is critical to safely guide evacuation efforts and to prevent accidents caused by congestion. In this paper, we focus on detecting the degree of crowd congestion following an earthquake based on information posted to Social Networking Services (SNSs). This research uses text data posted to Twitter just before/after the occurrence of the Great East Japan Earthquake (11 March 2011 at 02:46 PM JST). First, we extract co-occurring place names, proper nouns, and time-series information from tweets about congestion in the Tokyo metropolitan area (TMA). Next, using these extracted data, we analyze the frequency and spatiotemporal characteristics of these tweets. Finally, we identify expressions that describe the degree of crowd congestion and discuss methods to quantify these expressions based on a questionnaire survey and tweets that contain a photograph.
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