Connected Media Experiences Connectme proposal full title: Connected Media Experiences Proposal acronym



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FP7 ConnectME



Connected Media Experiences





ConnectME
Proposal full title:

Connected Media Experiences


Proposal acronym:

ConnectME


Type of funding scheme:

Integrated Project (IP)


Work programme topics addressed:

Challenge 1: Objective ICT-2009.1.5: Networked Media and 3D Internet



Target outcome c) Networked Search and Retrieval, partially also related to a) Content aware networks and network aware applications
Name of the coordinating person: Dr Rüdiger Klein, Fraunhofer IAIS

e-mail: ruediger.klein@iais.fraunhofer.de

fax: +49 2241 14 2342
List of participants:


Participant no. *

Participant organisation name

Part. short name


Country

Type

1 (Coordinator)

Fraunhofer IAIS

FRAUNHOFER

Germany

Public Research Center

2

Centre for Research and Technology Hellas – Informatics and Telematics Institute

CERTH

Greece

Public Research Center

3

University of Economics Prague

UEP

Czech Rep

University

4

Centrum Wiskunde & Informatica

CWI

Netherlands

Public Research Center

5

Eurecom

EURO

France

Public Research Center

6

University of St Gallen

USG

Switzerland

University

7

Semantic Technology Institute International

STI

Austria

Public Research Center


8

Condat

CONDAT

Germany

SME

9

Noterik

NOTERIK

Netherlands

SME

10

Sound and Vision

S+V

Netherlands

Public Company

11

Deutsche Welle

DW

Germany

Public Broadcaster

12

Rai Radiotelevisione Italiana

RAI

Italy

Public Broadcaster

13

Thomson Grass Valley

TGV

France

Industry

14

Samsung Korea (non-funded)

SAMSUNG

Korea

Industry

Abstract 6

Executive Summary 7

1.1 Concept and objectives 9


1.1.1 Project description 9

1.1.2 Project scenarios 13

Scenario 1: Cultural Heritage Research 14

Scenario 3: Family edutainment 17

1.1.3 Project objectives 20

Objectives by workpackage 21

1.1.4 Relation to call 22

1.2 Progress beyond the state-of-the-art 24



Web-based interactive video 24

IP-based interactive TV 25

1.2.1 Multimedia analysis 26

1.2.2 Web data mining 28

1.2.3 Multimedia annotation 29

Concept-based Multimedia Retrieval 29

Multimedia Fragment Addressing 29

1.2.4 Personalisation 30

User profiling 30

Related efforts in user profiling of multimedia content is limited to low-level profile representation, identifying preferences mostly in video genres and programme schedule. The ConnectME framework aims at identifying and handling more sophisticated user preferences based on advanced multimedia analysis and enriched metadata mining from Web resources. These preferences should be captured unobtrusively and be stored in lightweight semantic structures to provide computationally efficient, semantic content filtering for the PC,TV or handset. In addition, an efficient scheme of preference weighting, which is updated in time, is important, in order to distinguish the most prominent preferences in context and discern from long and short term interests. 30


Contextual adaptation 30

1.2.5 User interface 31

Summary of progress 32

1.3 S/T methodology and associated work plan 34

Architecture 34

Content side (broadcasters, archive holders, content owners)Content side (broadcaster) 34

Connected media: a supporting Internet infrastructure 35

Service side (telecommunications operators) 35

IPTV network and platform 35

End user device 36

Work Packages 36



Task 2.1: Media Fragments (EURECOM) 38

Task 2.2: Lightweight Metadata models for hypervideo (UEP) 38

Task 2.3: Web content mining and processing (UEP) 39

Task 3.1 User requirements analysis based on the 3 scenarios. 39

The tasks will relate directly to the three use cases and take into account the information sources being made available in WP1 & WP2. A number of tasks will be selected (in collaboration with content partners) for which innovative interfaces will be created in Task 3.2. 40

Task 3.2 User-centred design of hypervideo information interfaces 40

Task 3.3 Evaluate functionalities and interfaces of the connected media and background information. 40

Work package list 46


List of Deliverables 47

Gantt Chart 49

Work package descriptions 51

Summary of staff effort 60

List of milestones 61

Section 2. Implementation 62

2.1 Management structure and procedures 62



2.1.1 Project workplan structure 62

2.1.2 Management structure 62

2.1.3 Meetings and communication 63

2.1.4 Decision process 63

2.1.5 Conflict and risk management 64

2.1.6 Quality Management 66

2.1.7 Website and internal communication 66

Individual Participants 67


The group at UEP is recognised for its research and educational activities in knowledge discovery from databases, web/text/multimedia mining, web engineering and knowledge-based systems. It recently participated as funded partner in seven EU projects: in the multimedia area (6FP NoE K-Space), in the knowledge discovery from databases area (5FP projects Sol-Eu-Net and MiningMart), in the medical informatics area (4FP project MGT and DG SANCO project MedIEQ), in the e-learning area (6FP IP KP-Lab), and in the digital libraries area (eContent M-CAST). The group was involved in multiple EU network projects such as KDnet, Knowledge Web, Ontoweb or EUNITE, and its members participate in several W3C working groups. The group also host/ed top-class international conferences such as ECML (1997), PKDD (1999), EKAW (2006) and ISMIS (2009). The key expertise wrt. ConnectME is related to web mining and information extraction, as well as to the issues of multimedia-text analysis complementarity and multimedia metadata systems, which will be exploited in WP1 and WP2 of ConnectME. Web mining and information extraction was thoroughly studied in the EU MedIEQ project and in the national (CSF-funded) project Rainbow. In the EU K-Space project, in turn, UEP has been the leader of the task devoted to mining complementary resources to multimedia, and contributed to the development of the COMM – core ontology for multimedia. From KP-Lab UEP will bring the experience with text-based construction of shared domain models, and from M-CAST that with online question answering. 69


Dr. Raphaël Troncy is currently Assistant Professor in the multimedia information processing group of Eurecom (France). He obtained with honors his Master's thesis in Computer Science at the University Joseph Fourier of Grenoble (France), after one year spent in the University of Montreal (Canada). He benefited from a PhD fellowship at the National Audio-Visual Institute (INA) of Paris where he received with honors his PhD from the University of Grenoble (INRIA/INA) in 2004. He selected as an ERCIM Post-Doctorate Research Associate 2004-2006 where he visited the National Research Council (CNR) in Pisa (Italy) and the National Research Institute for Mathematics and Computer Science (CWI) in Amsterdam (The Netherlands). He was a senior researcher for CWI from 2006 till 2009. Raphaël Troncy is co-chair of the W3C Incubator Group on Multimedia Semantics and the W3C Media Fragments Working Group, contributes to the W3C Media Annotations Working Group and actively participates in the EU K-Space Network of Excellence. He is an expert in audio-visual metadata and in combining existing metadata standards (such as MPEG-7) with current Semantic Web technologies. He works closely with the IPTC standardisation body on the relationship between the NewsML language family and Semantic Web technologies. 70

Dr. Benoit Huet received his BSc degree in computer science and engineering from the Ecole Superieure de Technologie Electrique (Groupe ESIEE, France) in 1992. In 1993, he was awarded the MSc degree in Artificial Intelligence from the University of Westminster (UK) with distinction, where he then spent two years working as a research and teaching assistant. He received his DPhil degree in Computer Science from the University of York (UK) for his research on the topic of object recognition from large databases. He is currently Assistant Professor in the multimedia information processing group of Eurecom (France). His research interests include computer vision, content-based retrieval, multimedia data mining and indexing (still and/or moving images) and pattern recognition. He has published over 80 papers in journals, edited books and refereed conferences. He is a member of IEEE, ACM and ISIF. He has served in many international conference organization and technical program committee. He is regularly invited to serves as reviewer for prestigious scientific journals as well as expert for project proposal at national, European and International level. He is the conference chair of the International Conference on Multimedia Modeling (MMM'2009) which took place in Sophia-Antipolis (France) in January 2009. 70


Prof. Bernard Merialdo was admitted in the Ecole Normale Supérieure (Maths section) in 1975. He received a Ph.D. in Computer Science from Paris 6 University in 1979 and an "Habilitation à Diriger des Recherches" from Paris 7 University in 1992. He first taught at the Faculty of Sciences in Rabat (Morocco). In 1981, he joined the IBM France Scientific Center in Paris, where he led several research projects on natural language processing and speech recognition using probabilistic models. From 1988 to 1990, he was a visiting scientist in the IBM T.J Watson Research Center in Yorktown Heights, N.Y. (USA). In 1992, he became a professor in the Multimedia Communications Department of Eurecom. His current research topics are multimedia indexing and information filtering applications. He is a member of IEEE, ACM, he was associate editor for the IEEE Transaction on Multimedia, and general chair for the ACM Multimedia 2002 conference. He participates in several conference program committees and expert boards. He is currently Head of the Multimedia Communications Departement at Eurecom. 70

Kerstin Mathaj graduated in Diplom-Informatik (computer science) at the Technical University of Berlin in 2004. Her focus is the design and development of model-driven Internet- and mobile applications on the basis of application servers, web content management (CMS) and Semantic Web technology. She is familiar with Object-oriented methods for analysis and design (OMT, UML), SOA (Service Oriented Architectures), database design (Oracle, MySQL) and network search (Lucine). 72

Consortium as a whole 76

Resources to be committed 77

Section 3. Impact 79

3.1 Social and business impact 79

3.2 Social: strengthening digital society 79

3.3 Business: strengthening IPTV in Europe 80

3.4 Why Europe? 81

3.5. Why will we succeed? 81

3.2 Positioning with respect to the realisation of a long term vision in the ICT domain 82

The Networked Electronic Media vision of 2020 82

The long term outlook for Future Media Networks 82

3.3 Dissemination and exploitation of project results, and management of intellectual property 84



Section 4. Ethical Issues 91

ETHICAL ISSUES TABLE 93



References 94




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