Arthur R. Pope

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To recognize an object in an image one must have some internal model of how that object may appear. We show how to learn such a model from a series of training images depicting a class of objects, producing a model that represents a probability distribution over variation in object appearance. Features identified in an image through perceptual organization(More)
We describe how to model the appearance of a 3-D object using multiple views, learn such a model from training images, and use the model for object recognition. The model uses probability distributions to describe the range of possible variation in the object's appearance. These distributions are organized on two levels. Large variations are handled by(More)
We survey the main ideas behind recent research in model-based object recognition. The survey covers representations for models and images and the methods used to match them. Perceptual organization, the use of invariants, indexing schemes, and match verification are also reviewed. We conclude that there is still much room for improvement in the scope,(More)
We describe how to model the appearance of an object using multiple views, learn such a model from training images, and recognize objects with it. The model uses probability distributions to characterize the signi cance, position, and intrinsic measurements of various discrete features of appearance; it also describes topological relations among features.(More)
BACKGROUND Fibroblasts (FIBs) within the retro-orbital space of patients with Graves' disease (GOFs) express thyrotropin receptors (TSHRs) and are thought to be an orbital target of TSHR-stimulating autoantibodies in Graves' ophthalmopathy (GO). Recently, we developed a low molecular weight, drug-like TSHR antagonist (NCGC00229600) that inhibited TSHR(More)
OBJECTIVES The effectiveness of case-managed residential care (CMRC) in reducing substance abuse, increasing employment, decreasing homelessness, and improving health was examined. METHODS A five-year prospective experiment included 358 homeless addicted male veterans 3, 6, and 9 months during their enrollment and at 12, 18, and 24 months after the(More)