1. Multimedia Retrieval Evaluation - Dr. Martha Larson
Short description: Multimedia retrieval has long benefited from benchmarking initiatives that offer tasks to the research community. A task consists of a problem definition, a data set and ground truth against which solutions to the task are evaluated. Benchmarking benefits the research community by bringing scientists together in a productive mix of cooperation and competition that fights fragmentation and promotes efficient use of resources. This talk discusses multimedia retrieval benchmarks and the contribution that they make to multimedia research. In particular, the MediaEval benchmark (http://www.multimediaeval.org/) is introduced and typical tasks are described. MediaEval tasks emphasize social and language aspects to multimedia retrieval and are designed based on specific use scenarios. The tasks covered include: geo-coordinate prediction for video, violent scenes detection for movies and low-resource spoken term detection for the Spoken Web.
2. Growing lifelong musical soulmates: a playground for research on (inter)active, adaptive music-aware systems - Prof. Perfecto Herrera
Short description: In this presentation I will examine different achievements that, by means of their convergence, make possible to transcend traditional and limited concepts of music information retrieval. As MIR shifts its focus from “information” to “interaction” we are aimed towards applications that: i) actively learn from behaviour patterns, sensed data, multimodal sources, and from explicit interactive training episodes, ii) take care for the overall musical wellness of the user (by providing news about preferred artists, recommending unknown but likeable music, facilitating musical epiphanies, etc.), and iii) accompany users beyond the usual life-cycle of their physical devices and become supportive tools in critical stages of their development (e.g, adolescence or senescence), demanding and providing attention and care in order to grow and evolve their music awareness as users do.
3. Large-scale multimedia retrieval: distributing multimmodal interactive learning - Prof. Stéphane Marchand-Maillet (Viper group - University og Geneva)
Short description: Multimedia retrieval could largely be achieved thanks to user feedback interpretation. Machine learning strategies such as Boosting can be designed to help in performing information fusion to gather and exploit every piece of knowledge the user is providing to the system.
As a natural extension of these working mechanisms, we have more recently attacked the problem of scalability in multimedia retrieval. We look at how computation and information access may be scheduled over a network of computers with distributed storage to preserve the usability and usefulness of our tools when applied over large colections of items bearing multimodal information.
Here, we therefore emphasise and review both aspects of retrieval performance and robustness against the increase in the scale of the dataset and in the complexity of the data. We summarise our achievements that have already resulted into concrete developments.
Panel (July 19th, 11:30): Is it the end of research on multimedia information retrieval?
Moderated by Marcin Detinyecki.
Marta González (Tecnalia), M. Antònia Martí (CLiC), Andreas Nürnberger (OvGU) and Juan Cigarrán (NLP&IR).
Venue: Universitat de Barcelona - Facultat de Filologia. Gran Via de les Corts Catalanes, 585 (Metro Universitat). [SEE MAP]
Download call for papers as PDF | Download call for papers as DOC
Multimedia retrieval systems (for text, image, audio, video and mixed-media)
Theoretical foundations of multimedia retrieval and mining
Intelligent multimedia data modeling, indexing and structure extraction
Adaptive Hypermedia and web based systems
Metadata for multimedia retrieval
Multimedia and multi-modal mining
Semantic content analysis for multimedia
Multimedia Interaction and Dialogue Management
Sentiment Analysis and Affect Detection for Multimedia Content
Soft Computing in Multimedia Information Retrieval
Adaptive query languages
Similarity measures (especially user adaptive measures)
User and preference modeling (including feedback models)
Methods for adaptive data visualisation and user interfaces
May 30th, 2011 EXTENDED Paper submission deadline
June 27th, 2011 Notification of acceptance/rejection
July 3rd, 2011 Final paper submission
July 7th, 2011 Early registration deadline
July 18th, 2011 Workshop starts