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Large-scale digitisation of historical documents demands robust methods that cope with the presence of frequent distortions and noisy artefacts. This paper presents a hybrid text line segmentation method that uses a novel data structure and a rule base to combine the strengths of top-down and bottom-up approaches while minimising their weaknesses. The effectiveness of the proposed approach has been...
We propose a two phase line segmentation method for handwritten pre-modern densely written manuscripts. The proposed method combines the robustness of projection based methods with the flexibility of graph based methods. The result are cut-outs of the image containing each text line. Overlapping characters, help lines and degradation can create foreground elements spanning several lines that are hard...
We describe a mechanism based upon activity manifolds that map image data from more than one view to spatial pose. We learn the manifolds from training data which are motion capture data about real human subjects exercising the target actions. The nature of the training data allows the learned manifolds to conform naturally to multiple constraints, including (1) the body-part articulation constraint;...
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