Visual Recognition of Man-made Materials and Structures in an Office Environment

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dc.contributor.authorSong, Y. Z.en_US
dc.contributor.authorTown, C. P.en_US
dc.contributor.editorMike Chantleren_US
dc.date.accessioned2016-02-11T13:30:55Z
dc.date.available2016-02-11T13:30:55Z
dc.date.issued2005en_US
dc.description.abstractThis paper demonstrates a new approach towards object recognition founded on the development of Neural Network classifiers and Bayesian Networks. The mapping from segmented image region descriptors to semantically meaningful class membership terms is achieved using Neural Networks. Bayesian Networks are then employed to probabilistically detect objects within an image by means of relating region class labels and their surrounding environments. Furthermore, it makes use of an intermediate level of image representation and demonstrates how object recognition can be achieved in this way.en_US
dc.description.sectionheadersImage Matching, Recognition, and Retrievalen_US
dc.description.seriesinformationVision, Video, and Graphics (2005)en_US
dc.identifier.doi10.2312/vvg.20051021en_US
dc.identifier.isbn3-905673-57-6en_US
dc.identifier.pages159-166en_US
dc.identifier.urihttps://doi.org/10.2312/vvg.20051021en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.8 [Scene Analysis]en_US
dc.subjectObject recognitionen_US
dc.titleVisual Recognition of Man-made Materials and Structures in an Office Environmenten_US
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