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Tiêu đề Editorial Knowledge-Assisted Media Analysis for Interactive Multimedia Applications
Tác giả E. Izquierdo, Hyoung Joong Kim, Thomas Sikora
Trường học Queen Mary, University of London
Chuyên ngành Electronic Engineering
Thể loại Editorial
Năm xuất bản 2007
Thành phố London
Định dạng
Số trang 2
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Hindawi Publishing CorporationEURASIP Journal on Advances in Signal Processing Volume 2007, Article ID 36404, 2 pages doi:10.1155/2007/36404 Editorial Knowledge-Assisted Media Analysis f

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Hindawi Publishing Corporation

EURASIP Journal on Advances in Signal Processing

Volume 2007, Article ID 36404, 2 pages

doi:10.1155/2007/36404

Editorial

Knowledge-Assisted Media Analysis for Interactive

Multimedia Applications

E Izquierdo, 1 Hyoung Joong Kim, 2 and Thomas Sikora 3

1 Department of Electronic Engineering, Queen Mary, University of London, Mile End Road, London E1 4NS, UK

2 Department of Control and Instrumentation Engineering, Kangwon National University, 192 1 Hyoja2 Dong,

Kangwon Do 200 701, South Korea

3 Communication Systems Group, Technical University Berlin, Einstein Ufer 17, 10587 Berlin, Germany

Received 30 December 2007; Accepted 30 December 2007

Copyright © 2007 E Izquierdo et al This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Advances in technologies for new forms of interactive

mul-timedia services are driving the emergence of a digital world

which is transforming all aspects of how people consume and

interact with digital content This emergent digital world is

characterised by online access to knowledge resources and

services independently from location and time Here,

digi-tal services evolve in response to user behaviour, and

tech-nology adapts itself to user needs As a consequence, new

forms of interactive user-centred multimedia services

ma-terialise originating in turn new business models and

eco-nomic growth These services are underpinned by the

con-fluence of different research fields including knowledge

man-agement, data mining, and signal processing The

conver-gence of these areas is the key to many applications

in-cluding interactive TV, networked medical imaging,

vision-based surveillance, and multimedia visualisation, navigation,

search, and retrieval The latter is a crucial application since

the exponential growth of audiovisual data, along with the

critical lack of tools to record the data in a well-structured

form, is rendering vast portions of available useless content

This special issue reports the work related to the

devel-opment of innovative paradigms and tools that are

driv-ing technological advances and producdriv-ing new interactive

knowledge-assisted multimedia services After a thorough

re-view process, a total of nine papers were selected

The first three papers address the challenging problem

of analysis for annotation and retrieval In their paper, C.-C

Chiang et al propose a learning state approach for image

re-trieval The authors design a scheme of region-based image

representation based on concept units, which are integrated

with different types of feature spaces and with different

re-gion scales of image segmentation In the second paper by

Q Zhang and E Izquierdo, an object-oriented approach for semantic-based image retrieval is presented The goal is to identify key patterns of specific objects in the training data and to use them as object signatures Two important aspects

of semantic-based image retrieval are considered: retrieval

of images containing a given semantic concept and fusion

of different low-level features to achieve higher discrimina-tion power in the underlying classificadiscrimina-tion problem A mul-tiobjective optimisation technique is used to find a suitable multidescriptor space in which several low-level image prim-itives can be fused The paper by G Zaji´c et al describes

a content-based image retrieval system with relevance feed-back The approach uses dimensionality reduction Cluster-ing is achieved by comparison of magnitudes of descriptor components in a query

The next two papers are dedicated to the more spe-cific problem of image classification G Papadopoulos et

al combine global and local image information to achieve knowledge-assisted image classification The proposed learn-ing approach exploits knowledge in the form of ontology The ontology specifies the domain of interest, its subdo-mains, the concepts related to each subdomain, as well as contextual information Support Vector Machines are em-ployed in order to provide image classification to the on-tology subdomains based on global image descriptions In the second paper R Srikantaswamy and R Samuel propose

a fast and efficient algorithm for segmenting a face suitable for recognition from a video sequence The cluttered back-ground is first subtracted from each frame, in the foreback-ground regions a coarse face region is found using skin colour Then using a dynamic template matching approach, the face is ef-ficiently segmented

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2 EURASIP Journal on Advances in Signal Processing

The last four papers selected for the special issue

ad-dress different yet important areas of knowledge-based

me-dia analysis In their paper, J ´Calic and W Campbell

fo-cus on the visualisation of video summaries The authors

present a system for compact and intuitive video

summari-sation aimed at both high-end professional production

en-vironments and small-screen portable devices In the next

paper, S.-S Hung and D Liu propose a class of view-based

projection-generation methods for mining various frequent

sequential traversal patterns in the virtual environments The

frequent sequential traversal patterns are used to predict the

user navigation behaviour and, through a clustering scheme,

help reduce disk access time with proper patterns placement

into disk blocks A prototype system for selective

dissemina-tion of broadcast news is presented in the paper by R Amaral

et al The goal of this work is to study the impact of audio

preprocessing errors on the speech recognition module and

the impact of speech recognition errors on segmentation and

indexation The last paper by H Bredin and G Chollet

re-views recent works in the field of audiovisual speech More

specifically it looks at techniques developed to measure the

level of correspondence between audio and visual speech It

overviews the most common audio and visual speech

front-end processing, transformations performed on audio, visual,

or joint audiovisual feature spaces and the actual measure of

correspondence between audio and visual speech

ACKNOWLEDGMENTS

This special issue has assembled a small sample of

pa-pers originating from well-known research groups The

con-tributing authors were instrumental in the completion of the

special issue and the Guest Editors would like to thank all of

them The anonymous referees played a key role in the review

and selection process ensuring the special issue includes only

the submissions of the highest technical quality

E Izquierdo Hyoung Joong Kim Thomas Sikora

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