Special Session
Call for Papers
Special Session
on
Machine Learning with Multimedia
Data
AIMS AND SCOPE
The web, as
well as TV and radio archives and other sources, give access to a growing amount
of data in a large variety of formats and media modalities, often containing
useful information.However, much of this information is not easily accessible and
usable, be it for users or for automatic systems that could make use of
it.While information extraction from written text has seen great
advances and is used by search engines, news aggregators, opinion monitoring
systems, mail filters, and many more, access to information in other modalities
(audio, images, video, ...) is still a very difficult problem. Machine learning
is used with varying success for diverse tasks dealing with multimedia data, but
many problems remain, ranging from finding good machine readable representations
of the data, extracting higher level (semantic) features to the development of
machine learning algorithms capable of dealing with high-dimension
spatio-temporal data. An important aspect is also the integration of information
obtained from various modalities, and the possibility for cross-modal access to
information (e.g. textual querying of video recordings).
One
important aim of this session is to bring together researchers working on
different types of data, be it music, video, speech, images, and more.
These tasks have much in common, and we hope to promote communication
between researchers from these different fields.
Topics
This session would
solicit original research papers including but not limited to the
following:
- Low level feature extraction, selection and transformation
- High level feature extraction from multimedia/cross-media
- Semantic content analysis, classification, and automatic annotation
- Machine learning and statistical models for spoken document retrieval
- Speech recognition and speaker recognition
- User-access pattern monitoring, modeling, and prediction
- Learning and relevance feedback in multimedia retrieval
- Semi-supervised learning in multimedia data analysis
- Transfer or multitask learning in multimedia/cross-media data analysis
- Semantic organization/visualization of multimedia and cross-media data
IMPORTANT DATES
Paper Submission Deadline:
| July 15, 2011 July 30, 2011 |
Notification of acceptance:
| September 7, 2011 |
Camera-ready papers & Pre-registration:
| October 1, 2011 |
The ICMLA Conference:
| December 18-21, 2011
|
This special session will be held as part of the ICMLA’11 conference. Authors should submit papers through the main conference submission website. Papers must correspond to the requirements detailed in the instructions to authors. All conference submissions will be handled electronically. Detailed instructions for submitting the papers are provided on the conference home page at:
http://www.icmla-conference.org/icmla11/
Accepted
papers must be presented by one of the authors to be published in the conference
proceeding. If you have any questions, do not hesitate to direct your questions
to Jens Grivolla <jens.grivolla@barcelonamedia.org> or any of the other session organizers.
Special Session Organizers:
- Jens Grivolla (Barcelona Media Innovation Centre, Speech and Language
Processing Group, Spain)
- Cyril Laurier (Universitat Pompeu Fabra, Music Technology Group,
Spain)
Program Comittee Members:
- Joan Codina (Universitat Pompeu Fabra, Web Research Group, Spain)
- Hanna Lukashevich (Fraunhofer IDMT)
- Rafael Ramirez (Music Technology Group, Universitat Pompeu Fabra)
- Paul Lamere (The Echonest, USA)
- Roberto Basili (University of Roma, Tor Vergata)
- Adrian Ulges (Image Understanding and Pattern Recognition Research Group,
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern)
- Behrouz Saghafi Khadem (NTU)
- Chengcui Zhang (Department of Computer and Information Sciences, The
University of Alabama at Birmingham, AL, USA)
- Ching-Wei Chen (Media Technology Lab, Gracenote, Inc.)
- Christian Raymond (INSA/IRISA)
- Daniel Gärtner (Fraunhofer IDMT, Semantic Music Technologies)
- Elie El Khoury (IRIT, France)
- Marc El-Bèze (Laboratoire Informatique d'Avignon, France)
- Maria-cristina Marinescu (Department of Computer Science, Universidad
Carlos III de Madrid)
- Maurizio Montagnuolo (RAI, Italy)
- Pedro Mercado (Fraunhofer IDMT)
- Rafael E Banchs (Barcelona Media)
- Sam Davies (BBC R&D)
- Lin Yang (Google)