Résumé du livre

Informationen zum Autor Isabelle Bloch is Professor at the Ecole Nationale Supérieure des Télécommunications, Paris, France. Klappentext The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions). Zusammenfassung This books offers an overview of the general principles and specifics of information fusion in signal and image processing! as well as covering the main numerical methods (probabilistic approaches! fuzzy sets! and possibility theory and belief functions). Inhaltsverzeichnis Preface 11 Isabelle BLOCH Chapter 1. Definitions 13 Isabelle BLOCH and Henri MAÎTRE 1.1. Introduction 13 1.2. Choosing a definition 13 1.3. General characteristics of the data 16 1.4. Numerical/symbolic 19 1.4.1. Data and information 19 1.4.2. Processes 19 1.4.3. Representations 20 1.5. Fusion systems 20 1.6. Fusion in signal and image processing and fusion in other fields 22 1.7. Bibliography 23 Chapter 2. Fusion in Signal Processing 25 Jean-Pierre LE CADRE, Vincent NIMIER and Roger REYNAUD 2.1. Introduction 25 2.2. Objectives of fusion in signal processing 27 2.2.1. Estimation and calculation of a law a posteriori 28 2.2.2. Discriminating between several hypotheses and identifying 31 2.2.3. Controlling and supervising a data fusion chain 34 2.3. Problems and specificities of fusion in signal processing 37 2.3.1. Dynamic control 37 2.3.2. Quality of the information 42 2.3.3. Representativeness and accuracy of learning and a priori information 43 2.4. Bibliography 43 Chapter 3. Fusion in Image Processing 47 Isabelle BLOCH and Henri MAÎTRE 3.1. Objectives of fusion in image processing 47 3.2. Fusion situations 50 3.3. Data characteristics in image fusion 51 3.4. Constraints 54 3.5. Numerical and symbolic aspects in image fusion 55 3.6. Bibliography 56 Chapter 4. Fusion in Robotics 57 Michèle ROMBAUT 4.1. The necessity for fusion in robotics 57 4.2. Specific features of fusion in robotics 58 4.2.1.Constraints on the perception system 58 4.2.2. Proprioceptive and exteroceptive sensors 58 4.2.3. Interaction with the operator and symbolic interpretation 59 4.2.4. Time constraints 59 4.3. Characteristics of the data in robotics 61 4.3.1. Calibrating and changing the frame of reference 61 4.3.2. Types and levels of representation of the environment 62 4.4. Data fusion mechanisms 63 4.5. Bibliography 64 Chapter 5. Information and Knowledge Representation in Fusion Problems 65 Isabelle BLOCH and Henri MAÎTRE 5.1. Introduction 65 5.2. Processing information in fusion 65 5.3. Numerical representations of imperfect knowledge 67 5.4. Symbolic representation of imperfect knowledge 68 5.5. Knowledge-based systems 69 5.6. Reasoning modes and inference 73 5.7. Bibliography 74 Chapter 6. Probabilistic and Statistical Methods 77 Isabelle BLOCH, Jean-Pierre LE CADRE and Henri MAÎTRE 6.1. Introduction and general concepts 77 6.2. Information measurements 77 6.3. Modeling and estimation 79 6.4. Combination in a Bayesian framework 80 6.5. Combination as an estimation problem 80 6.6. Decisio...