Marco Bressan

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Several state-of-the-art Generic Visual Categorization (GVC) systems are built around a vocabulary of visual terms and characterize images with one histogram of visual word counts. We propose a novel and practical approach to GVC based on a universal vocabulary, which describes the content of all the considered classes of images, and class vocabularies(More)
In this paper, we present novel histogram adjustment methods for displaying high dynamic range image. We first present a global histogram adjustment based tone mapping operator, which well reproduces global contrast for high dynamic range images. We then segment images and carry out adaptive contrast adjustment using our global tone mapping operator in the(More)
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate(More)
In this paper we present a Travel Blog Assistant System that facilitates the travel blog writing by automatically selecting for each blog paragraph written by the user the most relevant images from an uploaded image set. In order to do this, the system first automatically adds metadata to the traveler’s photos based both on a Generic Visual Categorizer(More)
We propose a methodology to analyze and visualize the relationships and influences between painters. We build a graph where each painter is a node and an edge between two nodes is weighted by the painters' similarity. The similarity of two painters is measured as a function of the similarity between their paintings. Although the image representation we use(More)
We introduce a novel algorithm for local contrast enhancement. The algorithm exploits a background image which is estimated with an edge-preserving filter. The background image controls a gain which enhances important details hidden in underexposed regions of the input image. Our designs for the gain, edge-preserving filter and chrominance recovery avoid(More)
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