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A main theme in object detection are currently discriminative part-based models. The powerful model that combines all parts is then typically only feasible for few constituents, which are in turn iteratively trained to make them as strong as possible. We follow the opposite strategy by randomly sampling a large number of instance specific part classifiers. Due to their number, we cannot directly train...
Online searches in big image databases require sufficient results in feasible time. Digitization campaigns have simplified the access to a huge number of images in the field of art history, which can be analyzed by detecting duplicates and similar objects in the dataset. A high recall is essential for the evaluation and therefore the search method has to be robust against minor changes due to smearing...
In minimal invasive surgery (MIS) a complete and seamless inspection of organs, e.g. the urinary bladder, using video endoscopes is often required for diagnostics. Since the endoscope is usually guided by free-hand, it is difficult to ensure a sequence of seamless frame transitions. Also 2-D panoramic images showing an extended field of view (FOV) do not provide always reliable results, since their...
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