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Notice

AISB event Bulletin Item

CFP: IJCAI-09 Workshop on Cross-Media Information Access and Mining

http://www.cs.kuleuven.be/~liir/conferences/CIAM2009/

CALL FOR PAPERS
---------------

CIAM 2009

IJCAI-09 Workshop on Cross-Media Information Access and Mining

http://www.cs.kuleuven.be/~liir/conferences/CIAM2009/

First call for papers

The workshop will take place July 13, 2009 as part of the Twenty-first International Joint Conference on Artificial Intelligence, Pasadena Conference Center, California.
http://ijcai-09.org/

This event is sponsored by The International Joint Conferences on Artificial Intelligence (IJCAI), The Association for the Advancement of Artificial Intelligence (AAAI) and The Interdisciplinary Institute for Broadband Technology (IBBT).

Artificial intelligence (AI) simulates intelligent tasks performed by humans. One primordial task is the understanding and fusion of multiple inputs, for instance, when seeing the world around us, listening to speech and other audio sounds, and reading texts. Multimedia archives containing text, video, still images and audio (speech and other sounds) are quickly gaining importance (e.g., on the World Wide Web or privately held by broadcasting companies, publishing houses, libraries, musea, police and intelligence services, courtrooms, hospitals, etc.). Systems that access or mine this multimedia content should have the intellectual capability to relate the different information sources to each other, and to align and integrate the content. Indeed, more often than not the different modalities complement and disambiguate each other. Such technologies will form the basis for multimedia and cross-media information retrieval and mining.

This situation demands for solutions for cross-media processing and content recognition, where some fundamental problems are emerging topics of interest in the research community. First, content recognition in the visual, textual or audio medium is improved by exploiting cross-modal co-occurrences, especially when many instances can reinforce each other. Content recognized in one medium (e.g., text) can serve as weak annotation for content to be learned in another medium (e.g., the visual medium). This allows, for instance, to train a visual object recognition system for frequent objects without the need for manually labeled training data. Similarly, the visual medium can assist in the processing of textual sources. For instance, recognized visual actions might contribute to the ontological classification of certain verbs used in language. Gestures can complement speech as a visual reflection of the semantics of a discourse or conversation. And there are many other examples. Content recognition also entails content linking across media, where we deal with problems of cross-document coreferencing (or alignment) of, for instance, entities (e.g., persons, objects, locations), of actions performed by entities, of events, and of temporal and spatial forms of expression. Moreover, the initially identified alignments might bootstrap additional cross-modal "translations".

The purpose of this workshop is to bring together researchers from computer vision, sound processing, human language technology, computational linguistics, artificial intelligence, machine learning, reasoning, information retrieval, cognitive science and application communities. The workshop will bring fertilizing discussions and ideas about that will foster new interdisciplinary research avenues in artificial intelligence. It will encourage research into intelligent behavior and unify methodologies.

The workshop is open to all members of the AI community. The number of participants is however limited to 40. We welcome original papers and posters. They should show a clearly motivated interest or expertise in cross-media recognition, retrieval and mining, and discuss contributing and grounded ideas. We aim at obtaining a balanced selection of papers coming from the different disciplines involved, that clearly stress multimodal processing.

Topics of interest include, but are not limited to:
Cross-media mining and categorization
Cross-media search and question answering
Cross-media summarization
Cross-media linking of entities, attributes, objects, and actions
Cross-media emotion detection and genre classification
Alignment algorithms
Image auto-annotation
Image and video retrieval based on multi-modal cues
Recognition of semantic roles and frames in text, images and video
Recognition of narratives in text and video
Spatial and temporal recognition and resolution
Multimodal discourse analysis
Submissions in pdf format should be made online at

http://www.cs.kuleuven.be/~liir/conferences/CIAM2009/index.php?topic=submit



before March 13, 2009, 23:59 (midnight) UTC+1. Papers should not be more than 6 double-column pages long. Please follow the IJCAI formatting instructions and use the supplied Word templates or Latex sources. Formatting guidelines can be found at the IJCAI 2009 website. The reviewing process will be double-blind with each submission receiving at least three reviews. Papers will be selected for oral or poster sessions. All accepted papers (oral and poster) will be published in the workshop proceedings. We are also arranging a journal special issue for post-workshop publication of selected papers.

Organizing committee

Vittorio Ferrari, ETH Zurich (ferrari@vision.ee.ethz.ch)
Marie-Francine Moens, Katholieke Universiteit Leuven (sien.moens@cs.kuleuven.be)
Tinne Tuytelaars, Katholieke Universiteit Leuven (tinne.tuytelaars@esat.kuleuven.be)
Luc Van Gool, ETH Zurich (vangool@vision.ee.ethz.ch)

Program committee

Kobus Barnard, University of Arizona
Tamara Berg, Stony Brook, NY
Lou Boves, University Nijmegen
Trevor Darrell, UC Berkeley
Pinar Duygulu, Bilkent University
Jacob Eisenstein, Massachusetts Institute of Technology
Shen Gao, Institute for Infocomm Research
Kristen Grauman, University of Texas
Eduard Hovy, University of Southern California
Mirella Lapata, Edinburgh University
Mark Maybury, MITRE
Jian-Yun Nie, Universit de Montral
Chris Pal, University of Rochester
Alan Smeaton, Dublin City University
Cees Snoek, University of Amsterdam
Ben Taskar, University of Pennsylvania
Katerina Pastra, ILSP
Dan Roth, University of Illinois at Urbana-Champaign
Bill Triggs, CNRS
Hugo Van hamme, Katholieke Universiteit Leuven
Jakob Verbeek, INRIA
Andrew Zisserman, University of Oxford