Irina M. Ciortan

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The architecture of computational models of visual attention designed for videos is generally the result of a direct extension of techniques dedicated to static images. These models try to extract the salient areas of dynamic scenes (i.e. areas that may capture visual attention) by fusing static saliency maps computed frame per frame with saliency maps(More)
We present an automated light calibration pipeline for free-form acquisition of shape and reflectance of objects using common off-the-shelf illuminators, such as LED lights, that can be placed arbitrarily close to the objects. We acquire multiple digital photographs of the studied object shot from a stationary camera. In each photograph, a light is freely(More)
Several historical documents from the collection of the National Library of Oslo were acquired using a hyperspectral scanner. While each of the documents has its specific characteristics, requiring different image preprocessing steps, the common goal for all documents is to increase their legibility. The aim of this study is to show the advantage of(More)
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