1. Dynamic estimation of the discernment frame in belief function theory: Application to object detection
- Author
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Abdelaziz Kallel, Wafa Rekik, Ahmed Ben Hamida, Roger Reynaud, Sylvie Le Hégarat-Mascle, Institut d'électronique fondamentale (IEF), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Systèmes et Applications des Technologies de l'Information et de l'Energie (SATIE), École normale supérieure - Cachan (ENS Cachan)-Université Paris-Sud - Paris 11 (UP11)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École normale supérieure - Rennes (ENS Rennes)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Centre National de la Recherche Scientifique (CNRS), and École Nationale d'Ingénieurs de Sfax | National School of Engineers of Sfax (ENIS)
- Subjects
Information Systems and Management ,Context (language use) ,02 engineering and technology ,Machine learning ,computer.software_genre ,Power set ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] ,Theoretical Computer Science ,Artificial Intelligence ,0202 electrical engineering, electronic engineering, information engineering ,Discernment ,Set (psychology) ,Spurious relationship ,ComputingMilieux_MISCELLANEOUS ,Mathematics ,business.industry ,Frame (networking) ,020207 software engineering ,Function (mathematics) ,Object detection ,Computer Science Applications ,Control and Systems Engineering ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,computer ,Software - Abstract
Classification or estimation problems deal with decisions among different hypotheses. In several applications, the set of hypotheses may evolve with time and/or with context. Then, this work focuses on the problem of dynamic estimation and update of the discernment frame in the framework of belief function theory.Belief function theory is widely used in decision systems because of its ability to model both the imprecision and the uncertainty. Now, the problem of the discernment frame estimation is even more critical as the set of handled hypotheses is the power set of the discernment frame.This study describes a solution to update and adjust the discernment frame in a sequential way as new sources provide new pieces of information. Besides incompleteness, it is assumed that the current discernment frame may contain duplicated or spurious hypotheses. We thus propose new update mechanisms and we show on a practical application, namely video surveillance, how these mechanisms may be applied.
- Published
- 2015
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