Extracting the Essence from Sets of Images

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dc.contributor.authorAlexa, Marcen_US
dc.contributor.editorDouglas W. Cunningham and Gary Meyer and Laszlo Neumannen_US
dc.date.accessioned2013-10-22T07:39:42Z
dc.date.available2013-10-22T07:39:42Z
dc.date.issued2007en_US
dc.description.abstractWe use a set of photographs showing similar scenes as a model for a single photograph this scene. A distance measure for this model is defined by correlating the neigborhoods of pixels in similar positions. A cross analysis of the source images yields confidence values for their pixels. The confidence values together with the distances in pixels are used to steer a variable bandwidth mean shift algorithm that moves an arbitrary image towards one conforming with the model. Furthermore, distances are also used for a non-local means reconstruction of image areas that have no consistent explanation in the source images. This allows reconstructing images of scenes that are inconsistently documented in the source images, e.g. are occluded in the majority of images.en_US
dc.description.seriesinformationComputational Aesthetics in Graphics, Visualization, and Imagingen_US
dc.identifier.isbn978-3-905673-43-2en_US
dc.identifier.issn1816-0859en_US
dc.identifier.urihttps://doi.org/10.2312/COMPAESTH/COMPAESTH07/113-120en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture and Image Generationen_US
dc.titleExtracting the Essence from Sets of Imagesen_US
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CompAesth 07: Workshop on Computational Aesthetics