Báo cáo hóa học: "Editorial Knowledge-Assisted Media Analysis for Interactive Multimedia Applications" ppt

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Báo cáo hóa học: "Editorial Knowledge-Assisted Media Analysis for Interactive Multimedia Applications" ppt

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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, distr ibution, 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, a nd 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 producing 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- trie val. 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 classification 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 descr iptor components in a query. The next two pap ers 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 afastandefficient algorithm for seg menting a face suitable for recognition from a video sequence. The cluttered back- ground is first subtracted from each frame, in the foreground regions a coarse face region is found using skin colour. Then using a dynamic template matching approach, the face is ef- ficiently segmented. 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 . 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. 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. 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

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