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Abstract: We present a method for learning a set of generative models which are suitable for synthesizing views of scene features from arbitrary camera positions. The model is capable of generating maximum likelihood views of selected features, as well as a measure of the likelihood of a particular view from a particular camera position. Training the models involves regularizing observations of the features from known camera locations. The uncertainty of the model is evaluated using cross validation. The ... (Update)
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