Data Fusion: Concepts and Ideas by H B Mitchell

By H B Mitchell

This textbook presents a entire creation to the techniques and proposal of multisensor information fusion.
It is an widely revised moment version of the author's profitable e-book: "Multi-Sensor info Fusion:
An advent" which was once initially released via Springer-Verlag in 2007.
The major alterations within the new publication are:

New fabric: except one new bankruptcy there are nearly 30 new sections, 50 new examples and a hundred new references. even as, fabric that is out-of-date has been eradicated and the rest textual content has been rewritten for extra readability. Altogether, the hot ebook is sort of 70 pages
longer than the unique booklet.

Matlab code: the place acceptable we have now given information of Matlab code that could be downloaded from the global net. In a number of locations, the place such code isn't really on hand, we've incorporated Matlab code within the physique of the textual content.

Layout. The structure and typography has been revised. Examples and Matlab code now seem on a grey history for simple identity and advancd fabric is marked with an asterisk.

The publication is meant to be self-contained. No earlier wisdom of multi-sensor facts fusion is thought, even if a few familarity with the elemental instruments of linear algebra, calculus and straightforward chance is usually recommended.

Although conceptually uncomplicated, the learn of mult-sensor info fusion provides demanding situations which are detailed in the schooling of engineer or machine scientist. To develop into useful within the box the coed needs to get to grips with instruments taken from quite a lot of different topics
including: neural networks, sign processing, statistical estimation, monitoring algorithms, machine imaginative and prescient and regulate thought. All too frequently, the coed perspectives multi-sensor facts fusion as a miscellaneous collection of other procedures which undergo no dating to one another. against this, during this publication the techniques are unified through the use of a typical statistical framework. in this case, the underlying trend of relationships that exists among the various methodologies is made obvious.

The publication is illustrated with many real-life examples taken from a various diversity of functions and comprises an intensive checklist of contemporary references.

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Extra resources for Data Fusion: Concepts and Ideas

Example text

7 Shows the serial arrangement of multiple classification cells Cm , m ∈ {1, 2, 3}, in a threestage biometric identification scheme. Apart from the decision-boxes Dm , m ∈ {1, 2}, the architecture is identical to that shown in Fig. 6. The function of the box Dm is to determine whether or not a biometric measurement from sensor Sm+1 is required. 4 Iterative Network Fig. 8 represents an iterative network in which we re-introduce the result R as auxiliary knowledge into the fusion cell F. This network is generally used in applications which possess dynamical data sources.

MSc. thesis, Institut Technische Informatik, Technischen Universitat Wien (2002) 22. : Covariance consistency methods for fault-tolerant distributed data fusion. Inform. Fusion 4, 201–215 (2003) 23. : Data Fusion: Definitions and Architectures. Les Presses de l’Ecole des Mines, Paris (2002) 24. : (2001) An introduction to the Kalman filter. 1 Introduction The subject of this chapter is the common representational format. Conversion of all sensor observations to a common format is a basic requirement for all multisensor data fusion systems.

13). FV SV CV F R FA SA CA Fig. 13 Shows the hierarchical architecture for an audio-visual speech recognition system. The network consists of a single central fusion node F which receives input from an audio fusion node FA and a visual fusion node FV . These nodes receive, respectively, raw sensor data from the audio and visual sensors SA and SV and auxiliary data from the secondary classifiers CA and CV . 13. Track-to-Track Fusion [1]. Fig. 14 shows the implementation of the track-to-track fusion system using a hierarchical architecture (see Sect.

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