An enhanced content selection mechanism for personalization of video news programmes

In this paper, we propose a content selection framework that improves the users` experience when they are enriching or authoring pieces of news. This framework combines a variety of techniques to retrieve semantically related videos, based on a set of criteria which are specified automatically depending on the media`s constraints. The combination of different content selection mechanisms can improve the quality of the retrieved scenes, because each technique`s limitations are minimized by other techniques` strengths. We present an evaluation based on a number of experiments, which show that the retrieved results are better when all criteria are used at time.

Document engineering approaches toward scalable and structured multimedia, web and printable documents

Document engineering is the computer science discipline that investigates systems for documents in any form and in all media. As with the relationship between software engineering and software, document engineering is concerned with principles, tools and processes that improve our ability to create, manage, and maintain documents (http://www.documentengineering.org). The ACM Symposium on Document Engineering is an annual meeting of researchers active in document engineering: it is sponsored by ACM by means of the ACM SIGWEB Special Interest Group. In this editorial, we first point to work carried out in the context of document engineering, which are directly related to multimedia tools and applications. We conclude with a summary of the papers presented in this special issue.

Seamlessly integrating similarity queries in SQL

Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query language (SQL) does not provide effective support for such queries. This paper proposes an extension to SQL that seamlessly integrates syntactical constructions to express similarity predicates to the existing SQL syntax and describes the implementation of a similarity retrieval engine that allows posing similarity queries using the language extension in a relational DBM. The engine allows the evaluation of every aspect of the proposed extension, including the data definition language and data manipulation language statements, and employs metric access methods to accelerate the queries. Copyright (c) 2008 John Wiley & Sons, Ltd.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Multimedial instruktionsmetodik : en fallstudie kring multimedia i undervisningen

Multimedia är ett hett omdebatterat ämne både i och utanför skolan. Vad är det bra för och hur kan man använda det i undervisningen? Den frågan kan man finna svaret på i detta arbete genom att läsa detta arbete.Vi ger bakgrundsmaterial i form av en kvantitativ attitydundersökning kring lärare och IT.Syftet med detta arbete är att bidra till skolutveckling genom att lyfta fram didaktiska metoder inom multimedial instruktionsmetodik. Vidare kommer vi att försöka få ett svar på hur de förhåller sig till att använda sig av multimediala hjälpmedel i sin undervisning.Undersökningens metod har varit kvalitativa intervjuer med 11 informanter. Dessa kommer både från högskola och gymnasieskola. Informanterna kommer från olika pedagogiska yrken så som högskoleadjunkt, yrkeslärare, lektor och kärnämneslärare.I våra teoretiska utgångspunkter klargörs diskursen för detta examensarbete. Under inlärning beskrivs olika utvecklingspsykologiska teorier. Där beskrivs bland annat multimedia principen och lärstilar .Ur resultatet framkommer att användning av multimedia ser olika ut och att instruktionsanvändandet stämmer överens med våra teoretiska utgångspunkter.Vidare diskuteras mer generella aspekter av multimedial inlärning samt hur undervisning kan organiseras och genomföras med olika presentationshjälpmedel. Genom att använda multimedia i undervisningen får man variation, som gynnar helhetsbilden kring olika lärstilar.Multimedial instruktionsmetodik handlar om hur och varför man kan och bör använda multimediala hjälpmedel för att förbättra undervisningen. Vi belyser teorier som understödjer ett multimedialt användande inom undervisning. Vår fallstudie undersöker lärares användning och ger lärande exempel på multimedial instruktionsmetodik. Under diskussionen framkommer fler intressanta lärande exempel. Här finns också hänvisningar till tänkbara multimediala inspirationskällor. En sammanställning för fortsatt forskning inom området finns att tillgå i form av en bilaga.Slutligen ges förslag till framtida forskning inom området för detta examensarbete.