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- W68056218 abstract "AbstractThe descriptive vocabulary of proximity groups, curvilinear alignment, parallels, corners, closed regions, and coherent texture regions are all important components of visual structure in images, but they don’t go far enough. Labels for visual structure can become richer in at least two ways. They can reflect more domain knowledge, and they can invoke more complex computational processes than the grouping and partitioning operations that are the stock-in-trade of the field.This chapter highlights two research domains driving enriched visual labels for Perceptual Organization. First, Document image analysis has traditionally relied on strong domain models to perform the narrow pattern classification task of Optical Character Recognition. Open-ended markings such as sketchcs, annotations, and handwritten notes break existing systems, and challenge Perceptual Organization to extend our weaker (and therefore more general) models. Second, posterized images simplify imagery of complex scenes, enabling us to distill apart the ingredients of comprehensive interpretation. We can explore analysis of surface occlusion relations by developing appropriate vocabularies and soft constraint propagation techniques for labeling local overlap at L- and T-junctions. Then, considerations of surface coherence, transparency, motion, etc., can be mixed in incrementally.Keywordsperceptual organizationweak modelsstrong modelsgrouping and partitioningdocument image analysissketch analysiswhiteboard imageoccluding contourL-junctionT-junctionsurface segmentationtransparencyX-junctionlocal motion constraint" @default.
- W68056218 created "2016-06-24" @default.
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- W68056218 date "2000-01-01" @default.
- W68056218 modified "2023-09-24" @default.
- W68056218 title "Toward Richer Labels for Visual Structure" @default.
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- W68056218 doi "https://doi.org/10.1007/978-1-4615-4413-5_11" @default.
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