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Modeling of perceptual systems: a sensor fusion model with active perception
Örebro University, Department of Technology.
2002 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Örebro: Örebro universitetsbibliotek , 2002. , p. 48
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 6
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-4244ISBN: 91-7668-320-6 (print)OAI: oai:DiVA.org:oru-4244DiVA, id: diva2:138543
Available from: 2007-07-08 Created: 2007-07-08 Last updated: 2018-01-13Bibliographically approved
List of papers
1. ECG analysis: a new approach in human identification
Open this publication in new window or tab >>ECG analysis: a new approach in human identification
2001 (English)Manuscript (preprint) (Other academic)
Abstract [en]

In this paper a new approach in human identification is investigated, For this purpose, a standard 12-lead electrocardiogram (ECG) recorded during rest is used. Selected features extracted from the ECG are used to identify a person in a predetermined group. Multivariate analysis is used for the identification task. Experiments show that it is possible to identify a person by features extracted from one lead only. Hence, only three electrodes have to be attached on the person to be identified. This makes the method applicable without too much effort.

Keywords
data fusion, electrocardiogram (ECG), feature extraction, human identification, multivariate analysis
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-16067 (URN)000169439600022 ()
Available from: 2011-06-22 Created: 2011-06-22 Last updated: 2018-01-12Bibliographically approved
2. Multivariate sensor fusion by a neural network model
Open this publication in new window or tab >>Multivariate sensor fusion by a neural network model
(English)Manuscript (preprint) (Other academic)
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-16070 (URN)
Available from: 2011-06-22 Created: 2011-06-22 Last updated: 2018-01-12Bibliographically approved
3. Active perception for autonomous sensor systems: an emerging paradigm?
Open this publication in new window or tab >>Active perception for autonomous sensor systems: an emerging paradigm?
2000 (English)Manuscript (preprint) (Other academic)
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-16068 (URN)000165444800008 ()
Available from: 2011-06-22 Created: 2011-06-22 Last updated: 2018-01-12Bibliographically approved
4. Active perception in a sensor fusion model
Open this publication in new window or tab >>Active perception in a sensor fusion model
2002 (English)Manuscript (preprint) (Other academic)
Abstract [en]

During the last decades the research in the sensor fusion area has mainly been focused on fusion methods and feature selection methods. A possible further development in this area is to incorporate a process referred to as active perception. This means that the system is able to manipulate the sensing mechanisms to create a focus on selected information in the surrounding environment. This process may also be able to handle the feature selection process with respect to which features to be used and/or the number of features to use. This paper presents a model that contains a decision system based on active perception integrated with previous sensor fusion algorithms. The human body has perhaps one of the most advanced perceptual processing systems. The human perception process can be divided into sensation (measurement collection) and perception (interpret the surroundings). During the sensation process a huge amount of data is collected from different sensors that reflect the environment. The information has to be interpreted in an effective way, i.e. in the fusion process. The interpretation together with a decision system to control the sensors to focus on important information will correspond to the (active) perception process. The model presented in this paper capitalizes on the properties presented by the biological counterpart to achieve more human-like processes for a sensor fusion. Finally, the paper presents the testing of the model in two examples. The applications used have a safety approach of fire indication, identification and decision-making. The goal is to enlarge a conventional fire alarm system to not only detect fire, but also to propose different actions for a human in a dangerous area for example.

National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-16066 (URN)000176995000017 ()
Available from: 2011-06-22 Created: 2011-06-22 Last updated: 2018-01-12Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
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