International Workshop on Semantic Learning Applications in Multimedia (SLAM)

In association with CVPR 2006

Sponsored by



New York City, NY, USA
June 18, 2006

New! Program (.pdf) (.html)

Important Dates

Paper submission: 03/15/06
Notification of acceptance: 04/15/06
Receipt of camera ready copy: 04/24/06
Workshop: 06/18/06 (one day before CVPR)

Scope

The use of semantic knowledge in multimedia is rapidly becoming more widespread and significant. In areas such as multimedia content analysis, media integration, semantic cues and knowledge are being used to achieve performance that is not attainable by purely bottom-up, data-driven approaches. In many applications, meaningful multimedia content recognition is not possible without contextual, semantic support. However, many fundamental challenges still remain.

This workshop will bring together an interdisciplinary group of researchers in computer vision, speech/music recognition, knowledge representation and ontologies, machine learning, natural language and other areas to examine the issues and recent results in using semantic knowledge to enhance multimedia. Recent progress in machine learning has enabled the rigorous management of uncertainty in large-scale reasoning problems, and this has stimulated the use of semantic methods and reasoning in multimedia. Simultaneously, the natural language and artificial intelligence communities have developed large computational models and databases of semantic knowledge. The multimedia communities are using both evidential reasoning methods and semantic knowledgebases to fuse multiple data sources for intelligent multimedia content analysis, integration, and delivery.

Papers are solicited in all disciplines related to the central theme, including but not limited to:

Organization

General Chairs:

Tom Huang, University of Illinois at Urbana-Champaign
Jiebo Luo, Kodak Research Labs
Milind Naphade, IBM T J Watson Research Center

Program Committee:

Kobus Barnard, University of Arizona
Matthew Boutell, Rose-Hulman Institute of Technology
Christopher Brown, University of Rochester
Tat-Seng Chua, NUS
Li Deng, Microsoft Research
Ajay Divakaran, MERL
Tsuhan Chen, Carnegie Mellon University
Jianping Fan, University of North Carolina at Charlotte
Ling Guan, Ryerson University
Alan Hanjalic, Delft University of Technology
Anthony Hoogs, GE Global Research
Xian-Sheng Hua, Microsoft Research Asia
Horace Ip, City University of Hong Kong
Qiang Ji, Rensselaer Polytechnic Institute
Nebjosa Jojic, Microsoft Research
John Kender, Columbia
Jim Little, UBC
Nemanja Petrovic, Google, Inc.
Andreas Savakis, Rochester Institute of Technology
Nicu Sebe, U Amsterdam
Mubarak Shah, USF
John R. Smith, IBM
Qibin Sun, Institute for Infocomm Research (Singapore)
Qi Tian, University of Texas at San Antonio
James Wang, Pennsylvania State University
Yi Wu, Intel Research
Zhongfei Zhang, SUNY Binghamton
Song-Chun Zhu, UCLA

Paper Submission

In keeping with the spirit of a workshop, submitted papers may emphasize intellectual risks and argue for ideas that do not yet have comprehensive experimental support. Hence papers may not need describe fully developed algorithms, methods, or results as would normally be required for acceptance at CVPR.

Papers describing novel, unpublished research are solicited in the areas listed above and closely related topics. Reviewing will be by members of the program committee. Each paper will receive at least two reviews. Acceptance will be based on relevance to the workshop, novelty, and technical quality. Papers should be at most 8 pages in length, in the same style format as CVPR, and encoded as pdf.

All accepted papers will be included in the electronic CVPR proceedings. There will not be a hardcopy proceedings for this workshop.

NEW for Authors! Electronic Submission Instructions Please click on the link below to register with the EDAS conference management system:

http://edas.info/Tyn.php?c=4807

You may not have an account with EDAS yet. Please use your email address as the user name, and leave the password field blank. EDAS will then create an account and email you the password. Use the password to login to EDAS and upload your paper in PDF format. You may choose to show author information or not in the paper, and the reviews will be either open or blind accordingly.

Program

Sunday, Jun 18

8:30 AM - 8:40 AM

Welcome-Opening Remarks

Chairs: Tom Huang, Jiebo Luo, Milind Naphade

 

8:40 AM - 9:30 AM

Morning Keynote: Song-Chun Zhu, UCLA

Knowledge Representation and Learning Schemes for Large Object Categories

 

9:30 AM - 10:15 AM

Session 1: Semantic Scene Categorization

Factor Graphs for Region-based Whole-scene Classification

Matthew Boutell (Rose-Hulman Institute of Technology, USA); Jiebo Luo (Eastman Kodak Company, USA); Christopher Brown (University of Rochester, USA)

Robust Scene Categorization by Learning Image Statistics in Context

Jan van Gemert (University of Amsterdam, The Netherlands); Jan-Mark Geusebroek (University of Amsterdam, The Netherlands); Cor Veenman (University of Amsterdam, The Netherlands); Cees Snoek (University of Amsterdam, The Netherlands); Arnold Smeulders (University of Amsterdam, The Netherlands)

Improving Web-based Image Search via Content Based Clustering

Nadav Ben-Haim (UCSD, USA); Boris Babenko (University of California, San Diego, USA); Serge Belongie (UC San Diego, USA)

 

10:45 AM - 11:45 AM

Session 2: Semantic Event Recognition

Attribute Grammar-Based Event Recognition and Anomaly Detection

Seong-Wook Joo (University of Maryland, USA); Rama Chellappa (Univ. of Maryland, USA)

Emblem Detections by Tracking Facial Features

Atul Kanaujia (Rutgers University, USA)

Semantic Event Detection using Conditional Random Fields

Tao Wang (Intel China Research Center, P.R. China); Jianguo Li (Intel China Research Center, Beijing, P.R. China); Qian Diao (Intel China Research Center, Beijing, P.R. China); Wei Hu (Intel China Research Center, Intel Corporation, P.R. China); Yimin Zhang (Intel China Research Center, Canada); Carole Dulong (Intel, USA)

Specifying, Interpreting and Detecting High-level, Spatio-Temporal Composite Events in

Single and Multi-Camera Systems

Senem Velipasalar (Princeton University, USA); Lisa Brown (IBM T.J. Watson Research Center,USA); Arun Hampapur (IBM T.J. Watson, USA)

 

1:40 PM - 2:30 PM

Afternoon Keynote: John R. Smith, IBM Research

Machine Tagging of Multimedia Content

 

2:30 PM - 3:15 PM

Session 3: Semantic Ontology & Learning

Object Boundary Detection in Images using a Semantic Ontology

Anthony Hoogs (GE Global Research, USA); Roderic Collins (GE Global Research, USA)

Semantic Learning for Audio Applications: A Computer Vision Approach

Rahul Sukthankar (Intel Research Pittsburgh, USA); Yan Ke (Carnegie Mellon University, USA); Derek Hoiem (Carnegie Mellon University, USA)

Generalized Multiclass AdaBoost and Its Applications to Multimedia Classification

Wei Hao (Kodak, USA); Jiebo Luo (Eastman Kodak Company, USA)

 

3:45 PM - 4:45 PM

Session 4: Multimedia Annotation & Retrieval

Video Annotation by Active Learning and Cluster Tuning

Guo-Jun Qi (University of Science and Technology of China, P.R. China); Yan Song (University of Science and Technology of China, P.R. China); Xian-Sheng Hua (Microsoft Research Asia, P.R. China); Li-Rong Dai (University of Science and Technology of China,, P.R. China); Hong-Jiang Zhang (Microsoft Research Asia, P.R. China)

Automatic Video Annotation by Mining Speech Transcripts

Atulya Velivelli (University of Illinois, USA); Thomas Huang (University of Illinois at Urbana Champaign, USA)

Audio-Visual Foreground Extraction for Event Characterization

Marco Cristani (University of Verona, Italy); Manuele Bicego (University of Sassari, Italy); Vittorio Murino (University of Verona, Italy)

Assessing the Filtering and Browsing Utility of Automatic Semantic Concepts for Multimedia Retrieval

Michael Christel (Carnegie Mellon University, USA); Milind Naphade (IBM T J Watson Research Center, USA)

 

4:45 PM - 5:30 PM

Panel Discussion

Panel: Tom Huang (UIUC), Jiebo Luo (Kodak), Milind Naphade (IBM), Anthony Hoogs (GE), John Smith (IBM), Song-Chun Zhu (UCLA)