A framework dealing with Uncertainty for Complex Event Recognition

International audienceThis paper presents a constraint-based approach for video complex event recognition with probabilistic reasoning for handling uncertainty. The main advantage of constraint-based approaches is the possibility for human expert to model composite events with complex temporal constraints. But the approaches are usually deterministic and do not enable the convenient mechanism of probability reasoning to handle the uncertainty. The first advantage of the proposed approach is the ability to model and recognize a large amount of composite events with complex temporal constraints. The second advantage is that probability theory provides a consistent framework for dealing with uncertain knowledge for a robust and reliable recognition of complex event. This approach is evaluated with 4 real healthcare videos and a public video database ETISEO'06. The results are compared with state of the art method. The comparison shows that the proposed approach improves significantly the process of recognition and characterizes the likelihood of the recognized events

Probabilistic Recognition of Complex Event

International audienceAbstract. This paper describes a complex event recognition approach with probabilistic reasoning for handling uncertainty. The first advantage of the proposed approach is the flexibility of the modeling of composite events with complex temporal constraints. The second advantage is the use of probability theory providing a consistent framework for dealing with uncertain knowledge for the recognition of complex events. The experimental results show that our system can successfully improve the event recognition rate. We conclude by comparing our algorithm with the state of the art and showing how the definition of event models and the probabilistic reasoning can influence the results of the real-time event recognition

Activity Recognition and Uncertain Knowledge in Video Scenes

International audienceActivity recognition has been a growing research topic in the last years and its application varies from auto-matic recognition of social interaction such as shaking hands, parking lot surveillance, traffic monitoring and the detection of abandoned luggage. This paper describes a probabilistic framework for uncertainty handling in a description-based event recognition approach. The proposed approach allows the flexible modeling of composite events with complex temporal constraints. It uses probability theory to provide a consistent framework for dealing with uncertain knowledge for the recognition of complex events. We validate the event recognition accuracy of the proposed algorithm on real-world videos. The experimental results show that our system can successfully recognize activities with a high recognition rate. We conclude by comparing our algorithm with the state of the art and showing how the definition of event models and the probabilistic reasoning can influence the results of real-time event recognitio

FUSION FRAMEWORK FOR VIDEO EVENT RECOGNITION

International audienceThis paper presents a multisensor fusion framework for video activities recognition based on statistical reasoning and D-S evidence theory. Precisely, the framework consists in the combination of the events' uncertainty computation with the trained database and the fusion method based on the conflict management of evidences. Our framework aims to build Multisensor fusion architecture for event recognition by combining sensors, dealing with conflicting recognition, and improving their performance. According to a complex event's hierarchy, Primitive state is chosen as our target event in the framework. A RGB camera and a RGB-D camera are used to recognise a person's basic activities in the scene. The main convenience of the proposed framework is that it firstly allows adding easily more possible events into the system with a complete structure for handling uncertainty. And secondly, the inference of Dempster-Shafer theory resembles human perception and fits for uncertainty and conflict management with incomplete information. The cross-validation of real-world data (10 persons) is carried out using the proposed framework, and the evaluation shows promising results that the fusion approach has an average sensitivity of 93.31% and an average precision of 86.7%. These results are better than the ones when only one camera is used, encouraging further research focusing on the combination of more sensors with more events, as well as the optimization of the parameters in the framework for improvements

Organisational ineffectiveness: environmental shifts and the transition to crisis

Purpose: – The purpose of this paper is to explore the notion of effectiveness in the context of organisational crisis. It considers the “darker” side of organisational effectiveness by exploring the processes by which effectiveness can be eroded as an organisation moves from an ordered state, through a complex one, and into a state of chaos, or crisis. It brings together complementary literatures on risk, crisis management, and complexity, and uses those lenses to frame some of the key processes that allow organisations to transition to a state that shapes their inabilities to remain effective.<p></p> Design/methodology/approach: – The paper sets out a theoretical framework for the analysis of a crisis event and does so in a way that emphasises the role of the human element in the various stages of a crisis: the incubation phase, the operational crisis, and the post-event legitimation phase. The paper uses the emerging crisis around the disappearance of Malaysia Airlines flight MH370 to illustrate some of the task demands associated with a crisis and the manner in which crisis events challenge the efficiencies and capabilities of organisations to deal with complex, multi-layered issues in which uncertainty is high. Given the emergent nature of that particular crisis, the use of the case is purely illustrative rather than analytically grounded in a normal case study approach.<p></p> Findings: – The paper highlights a number of underlying elements that contribute to the generation of crises and offers recommendations for managers on how to deal with those demands. The paper shows how an organisation can move from an ordered state into a complex or chaotic one and highlights some of the problems that arise when an organisation does not have the capabilities to respond to the task demands generated by such a shift in the environment.<p></p> Practical implications: – The paper challenges some of the normal practices of management in a “steady state” environment and highlights the need to consider the organisational capabilities that are necessary to deal with the transition from a stable to an unstable system state and ensure organisational effectiveness in the process. A core message within the paper is that the “normal” processes of management can contribute to the generation of crises as organisations prioritise short-term efficiencies over the strategies for longer-term effectiveness. The implications for crisis management practices are discussed. Social implications – The paper considers an issue that has wider applicability within society namely the relationships between organisational effectiveness and risk. The issues raised in the paper have applicability in a range of other societal settings.<p></p> Originality/value: – The key output from the paper is the development of a theoretical framework that allows for an analysis of the relationships between crises and organisational effectiveness. The paper argues that effectiveness and crisis management are intrinsically linked and that crises occur when organisational effectiveness is impaired. The paper highlights the role that template-based approaches to dealing with complex problems can have in terms of the generation of crisis events

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Food security, risk management and climate change

This report identifies major constraints to the adaptive capacity of food organisations operating in Australia. This report is about food security, climate change and risk management. Australia has enjoyed an unprecedented level of food security for more than half a century, but there are new uncertainties emerging and it would be unrealistic – if not complacent – to assume the same level of food security will persist simply because of recent history. The project collected data from more than 36 case study organisations (both foreign and local) operating in the Australian food-supply chain, and found that for many businesses,  risk management practices require substantial improvement to cope with and exploit the uncertainties that lie ahead. Three risks were identified as major constraints to adaptive capacity of food organisations operating in Australia:  risk management practices; an uncertain regulatory environment – itself a result of gaps in risk management; climate change uncertainty and projections about climate change impacts, also related to risk management

Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment