Multi-Sensor Data Fusion
An Introduction

Self-contained, easy accessible introduction to multi-sensor data fusion for graduate students and researchers

Well-organized modern approach to theories and techniques, includes numerous case studies that illustrate the application of techniques for multi-sensor data fusion to real problems, providing hands-on knowledge

The case studies cover a very wide range of applications – including medical imaging, geoscience applications, biometric identification, pattern classification, handwriting analysis, target tracking, computer vision etc.

Presents the first unified treatment of the subject using a Bayesian probabilistic framework

Contains details of MATLAB software programs which are available for all the multi-sensor data fusion techniques used in the book

Includes extensive modern bibliography containing more than 400 references of which more than 60% were published in the year 2000 or later