Post processing of multimedia information - concepts, problems, and techniques

Currently, most research work on multimedia information processing is focused on multimedia information storage and retrieval, especially indexing and content-based access of multimedia information. We consider multimedia information processing should include one more level-post-processing. Here &quot;post-processing&quot; means further processing of retrieved multimedia information, which includes fusion of multimedia information and reasoning with multimedia information to reach new conclusions. In this paper, the three levels of multimedia information processing storage, retrieval, and post-processing- are discussed. The concepts and problems of multimedia information post-processing are identified. Potential techniques that can be used in post-processing are suggested, By highlighting the problems in multimedia information post-processing, hopefully this paper will stimulate further research on this important but ignored topic.<br /

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Beyond ECDL: basic and advanced IT skills for the new library professional

This paper reports on a new multimedia-centred ICT module, called Fundamentals of Information and Communication Technology (FICT) for Postgraduate Information and Library Studies students at the Graduate School of Informatics at Strathclyde University. It had radical aims (introducing novel ICT skill content in a progressive manner, encouraging deep learning and self-directed study) and used a weekly survey and a post-module survey to investigate its operation. Skills learnt were compared to skills required during student placement in libraries. Conclusions are drawn as to its success in matching the needs of future library professionals

The relationship between IR and multimedia databases

Modern extensible database systems support multimedia data through ADTs. However, because of the problems with multimedia query formulation, this support is not sufficient.\ud \ud Multimedia querying requires an iterative search process involving many different representations of the objects in the database. The support that is needed is very similar to the processes in information retrieval.\ud \ud Based on this observation, we develop the miRRor architecture for multimedia query processing. We design a layered framework based on information retrieval techniques, to provide a usable query interface to the multimedia database.\ud \ud First, we introduce a concept layer to enable reasoning over low-level concepts in the database.\ud \ud Second, we add an evidential reasoning layer as an intermediate between the user and the concept layer.\ud \ud Third, we add the functionality to process the users' relevance feedback.\ud \ud We then adapt the inference network model from text retrieval to an evidential reasoning model for multimedia query processing.\ud \ud We conclude with an outline for implementation of miRRor on top of the Monet extensible database system

Image mining: issues, frameworks and techniques

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. Despite the development of many applications and algorithms in the individual research fields cited above, research in image mining is still in its infancy. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining at the end of this paper

The academic atudies between printed and multimedia text in Italy

La diffusione e la disponibilità di testi e fonti informative rese disponibili e immediatamente fruibili attraverso la rete ha reso disponibili banche dati testi di diversa natura, in generale facilitato l'accesso a diversi tipi di documentazione (Gui 2014) e incrementato il tempo dedicato alla lettura (Bohn e Short 2009). Inoltre Internet in quanto fonte informativa occupa un posto di fondamentale importanza nei sistemi di istruzione e formazione. In Italia con la Legge 107/2015 il Ministero dell’Istruzione, dell’Università e della Ricerca ha messo a punto un Piano Nazionale Scuola Digitale (PNSD) sostenendo di fatto un processo di dematerializzazione del libro nel sistema di istruzione, ormai avviato e spesso ritenuto soluzione didattica. Tuttavia questo processo non è esente da rischi. Come sottolinea Casati (2013) il libro di carta presenta una indubbi vantaggi cognitivi connessi a linearità, stabilità della pagina che offre i contenuti, modalità di lettura. A ciò possiamo aggiungere gli elementi critici connessi al sistema di ricerca in Internet (Spitzer 2015) e le difficoltà di selezione delle fonti e del contenuto informativo connesse a tale ricerca. In questa sede si propone di sviluppare il tema attraverso una analisi critica anche alla luce delle evidenze emerse nel corso delle interviste a un gruppo di laureandi iscritti al corso di laurea triennale in Scienze dell’Educazione e della Formazione (SEF) dell'Università di Roma "La Sapienza"This essay falls within the reflection on the relation between learning places and methods and the use of new technologies in Italy. The diffusion and immediate availability of texts and sources of information through the Internet have enabled the access to various databases of texts as well as to several types of documentation, thus increasing the time spent on reading [1]. Moreover, the Internet-intended as a source of information -plays a crucial role within the education and training systems. In Italy, Law 107/2015 of the Ministry of Education, Universities and Research (MIUR) has provided for a National Plan for Digital Education (PNSD) which promotes the dematerialization of books with in the school system, often regarded as proven educational instruments. However this process necessarily involves some risks. As evidenced by Casati (2013) [2], printed books have clear cognitive advantages thanks to their linearity, the stability of the page bearing the contents, and the ease of reading. This could be supplemented by critical elements relating to the research on the Internet [3] and the difficulty of selecting the sources and the information highlighted by the research. In this context, the issue is developed also based on the evidences arisen from the interviews with some students about to graduate in Education and Training (SEF) - 1st level degree - at The Sapienza University of Rom

Enhanced journals - a case study with general remarks

The Information Bulletin on Variable Stars - a small astronomy journal published in Hungary - was an early Open Access journal. Now it offers several enhanced features to its reader community. Relying on the rather unique publishing environment existing in the field of astronomy, and on software developed locally, this journal is markedly different from other enhanced journals in certain aspects. We explore the key features of enhanced and common electronic journals: reference linking, database connections, data linking, multi-media content, feedback from the reader community, quality control. We argue that while exploring new avenues of scientific publishing, one should conservatively preserve some traditional values and features. Some aspects of article disassembly - dealing with items smaller than the usual basic publication unit, the article - are explored too. Figures, for example, are article components which might be re-used, used outside the original context

The design of an Image Bank

Image Banks, which are collections of images with associated data and captions, are a valuable teaching tool for Astronomy courses at the Open University. Until now web pages have been created for each image and its associated information. This paper examines how a database, front-ended by a multimedia authoring tool, can provide a much more flexible and maintainable architecture for producing Image Banks. Accessibility issues are discussed

Direct kernel biased discriminant analysis: a new content-based image retrieval relevance feedback algorithm

In recent years, a variety of relevance feedback (RF) schemes have been developed to improve the performance of content-based image retrieval (CBIR). Given user feedback information, the key to a RF scheme is how to select a subset of image features to construct a suitable dissimilarity measure. Among various RF schemes, biased discriminant analysis (BDA) based RF is one of the most promising. It is based on the observation that all positive samples are alike, while in general each negative sample is negative in its own way. However, to use BDA, the small sample size (SSS) problem is a big challenge, as users tend to give a small number of feedback samples. To explore solutions to this issue, this paper proposes a direct kernel BDA (DKBDA), which is less sensitive to SSS. An incremental DKBDA (IDKBDA) is also developed to speed up the analysis. Experimental results are reported on a real-world image collection to demonstrate that the proposed methods outperform the traditional kernel BDA (KBDA) and the support vector machine (SVM) based RF algorithms