Object detection, segmentation and visual tracking are extremely important problems in both computer vision and medical image analysis. In this thesis I will show how voting strategies can be used to tackle detection, segmentation and pose estimation problems relying on voting strategies which look only at image parts and assemble the resulting knowledge into a global decision. This approach overcomes the limitation of current machine learning methods in all those cases where the uncertainty of the decision over previously unseen data remains high.
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Object detection, segmentation and visual tracking are extremely important problems in both computer vision and medical image analysis. In this thesis I will show how voting strategies can be used to tackle detection, segmentation and pose estimation problems relying on voting strategies which look only at image parts and assemble the resulting knowledge into a global decision. This approach overcomes the limitation of current machine learning methods in all those cases where the uncertainty of...
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