Statistical pattern recognition techniques for target differentiation using infrared sensor

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dc.citation.epage473en_US
dc.citation.spage468en_US
dc.contributor.authorAytaç, Tayfunen_US
dc.contributor.authorYüzbaşıoğlu, Ç.en_US
dc.contributor.authorBarshan, Billuren_US
dc.coverage.spatialHeidelberg, Germanyen_US
dc.date.accessioned2016-02-08T11:46:54Z
dc.date.available2016-02-08T11:46:54Z
dc.date.issued2006en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 3-6 September 2006en_US
dc.descriptionConference Name: International Conference on Multisensor Fusion and Integration for Intelligent Systems, IEEE 2006en_US
dc.description.abstractThis study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.en_US
dc.identifier.doi10.1109/MFI.2006.265631en_US
dc.identifier.urihttp://hdl.handle.net/11693/27182
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/MFI.2006.265631en_US
dc.source.titleProceedings of the International Conference on Multisensor Fusion and Integration for Intelligent Systems, IEEE 2006en_US
dc.subjectInformation retrievalen_US
dc.subjectMeasurement theoryen_US
dc.subjectParameter estimationen_US
dc.subjectPattern recognitionen_US
dc.subjectStatistical methodsen_US
dc.subjectTarget trackingen_US
dc.subjectInfrared sensoren_US
dc.subjectStatistical pattern recognition techniquesen_US
dc.subjectSensorsen_US
dc.titleStatistical pattern recognition techniques for target differentiation using infrared sensoren_US
dc.typeConference Paperen_US

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