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Robert P.W. Duin studied applied physics at Delft University of Technology in the Netherlands. In 1978 he received the Ph.D. degree for a thesis on the accuracy of statistical pattern recognizers. In his research he included various aspects of the automatic nterpretation of measurements,learning systems and classifiers. Between 1980 and 1990 he studied and developed hardware architectures and software configurations for interactive image analysis. After this period his interest was redirected via neural networks to pattern recognition.

At this moment he is an associate professor of the Faculty of Electrical Engineering, Mathematics and Computer Science of Delft University of Technology. His present research is in the design, evaluation and application of algorithms that learn from examples. This includes neural network classifiers, support vector machines, classifier combining strategies and one-class classifiers. Especially complexity issues and the learning behavior of trainable systems receives much interest. Recently he started to investigate alternative object representations for classification and he became thereby interested in dissimilarity based pattern recognition, trainable similarities and the handling of non-Euclidean data. He expects that this will contribute to the unification of learning from structure and learning from statistics.

The pattern recognition research team headed by Robert Duin studies many industrial and medical applications. They are thereby interested in pattern recognition system design, the handling of ill-sampled problems and in varying costs and prior probabilities. A series of pattern recognition courses for industry has been set up by this team. The software (PRTools) is public available for research purposes.

Robert Duin is a former associate editor of IEEE Transactions on Pattern Analysis and Machine Intelligence. Presently he is an advisory editor of Pattern Recognition Letters. He is a member of the IEEE, and a fellow of the IAPR. In August 2006 he received the Pierre Devijver Award for his contributions to statistical pattern recognition.

Dr. Apostol (Paul) Natsev is a Research Staff Member and Manager of the Multimedia Research Group at the IBM T. J. Watson Research Center. He received his M.S. (1997) and Ph.D. (2001) degrees in Computer Science from Duke University, and joined IBM Research in 2001. At IBM, he leads research efforts on multimedia analysis and retrieval, with an agenda to advance the science and practice of systems that enable users to manage and search vast repositories of unstructured multimedia content.

Dr. Natsev is a founding member and senior researcher of IBM's award- winning MARVEL project on multimedia analysis and retrieval, with pioneering contributions in the area of content-based and semantic concept-based multimedia retrieval. He is an active participant in the NIST TREC Video Retrieval (TRECVID) evaluation, and leads the IBM video search team, which has achieved excellent performance in TRECVID several years in a row (in 2006, TRECVID involved an estimated 380 researchers from almost 100 separate institutions world-wide). He is also the chief architect and lead developer of the MARVEL-based video fingerprinting and copy detection system, which achieved top performance in the 2007 CIVR Video Copy Detection Showcase.

Dr. Natsev is an author of more than 60 publications and 15 U.S. patents (4 granted, 11 pending) in the areas of multimedia analysis, indexing and search, multimedia databases and query optimization. His research has been recognized with several awards, including the 2004 Wall Street Journal Innovation Award (for MARVEL multimedia analysis and retrieval system), an IBM Outstanding Technical Accomplishment Award in 2005 (also for MARVEL), a 2005 ACM Multimedia Plenary Paper Award, and a 2006 ICME Best Poster Award.

Joost van de Weijer is a Ramon y Cajal fellow at the Computer Vision Center in Barcelona. He received his M.Sc. degree in applied physics at Delft University of Technology in 1998. In 2005, he obtained the Ph.D. degree at the University of Amsterdam. During 2005-2007 he was a Marie Curie Intra-European Fellow in the LEAR team at INRIA Rhône-Alpes in France. He is currently involved in research on the application of color to bag-of-word approaches for object recognition, image classification and image retrieval.

Joost van de Weijer research has focused primarily on the application of color to computer vision. Color information is both investigated from a physical perspective as from a human vision viewpoint. He has made contributions to color constancy, color feature detection, color feature extraction, and color saliency theory. More recently he has performed research on the application of learning techniques to solve more complex color imaging problems, such as the automatic learning of color names from image search engines and top-down color constancy.

Cristian Sminchisescu is running a research group at the University of Bonn , and he is Adjunct Professor in the Artificial Intelligence Lab at the University of Toronto and TTI-C . During 1999-2002 I've been with the MOVI (now PERCEPTION and LEAR ) research group at INRIA , where I obtained a doctorate in Computer Science and Applied Mathematics, with a specialization in Imaging, Vision and Robotics. During this period, I collaborated in the EU project VIBES on Video Browsing, Exploration and Structuring. I spent the next two years, 2003-2004, as a research fellow in the AI Lab at the University of Toronto , working on computer vision and probabilistic modeling.

Cristian Sminchisescu studies problems at the incidence of computer vision, machine learning and computer graphics. He has scientific interests in fundamental non-convex optimization and sampling algorithms and probabilistic modeling, but also in pattern recognition methods for visual scene understanding, in particular: 1) 3d human motion analysis and time series models ; 2) object recognition and localization , and 3) shape modeling . Over time, my work has been funded by the EU, The French Ministry of Foreign Affairs, NSERC, NSF and TTI-C.

He is probably better known for the work in 3 d human motion reconstruction from monocular video, on which he gave tutorials at IEEE CVPR 2006, ICCV 2005 and the Chicago Machine Learning Summer School, in 2005. He was involved in co-organizing a workshop on Learning, Representation and Context for Human Sensing in Video at CVPR 2006.

Mohan Trivedi

Mohan Trivedi is a Professor in the Electrical and Computer Engineering Department and serves as the Director of the Computer Vision and Robotics Research Laboratory. He and his team are engaged in a broad range of research studies, which include active perception and novel machine vision systems, intelligent ("smart") environments, distributed video networks and intelligent systems.

His team's recent research involvement and accomplishments include: a new framework for efficient means of extraction and integration of multiple depth cues; a novel multimodal interface for modeling and monitoring composition and activity in an "intelligent room", development of cooperating mobile robot teams; computational models for texture analysis and synthesis; an integrated robotic system for applications in nuclear environments and for inspection and maintenance of high-speed railway (Shinkansen) tracks; a real time machine vision system for detection and classification of very small marine organisms in the ocean; and a distributed intelligent system for traffic incidence monitoring and mitigation. He has been published extensively and has edited over a dozen volumes including books, special issues, video presentations, and conference proceedings.

Trivedi serves as a charter member of the Executive Committee of the University of California System wide Digital Media Innovation Program (DiMI) (http://www.dimi.ucsb.edu/). He also serves on the Executive Committee of the California Institute for Telecommunication and Information Technologies (Cal-(IT)2) (http://www.calit2.net/) as the leader of the UCSD's Intelligent Transportation and Telematics Team. He serves regularly as a consultant to industry and government agencies in the USA and abroad.

Rita Cucchiara

Rita Cucchiara is Full Professor in Computer Engineering at the Faculty of Engineering, University of Modena. Her current interests include pattern recognition and computer vision for video surveillance, medical imaging, and multimedia. In multimedia she worked in models for semantic transcoding of videos. Now, she is involved in researches on video annotation and MPEG-7 video access. Medical imaging researches are oriented to colour analysis for skin lesion and melanoma classification. Video surveillance activity is devoted to new models of object segmentation, shadow detection, tracking, and people behaviour analysis indoor and outdoor applications. Eventually, these models are applied in intelligent transportation systems for traffic control.

She is responsible of many Italian and International projects. Currently, she is responsible of a Research Unit in the “ European Network of Excellence on Digital Library” DELOS EU VI FP 2004-2008, and in Italian PRIN (Progetti di Rilevante Interesse Nazionale) for skin lesion analysis (2004-2006); she is scientific coordinator of the Regional Project LAICA (Laboratorio di Ambient Intelligent per una citta’ amica) with the Region Emilia Romagna and manages many projects with private companies (e.g. Traficon Belgium, world leader in traffic surveillance). Moreover, she is co-responsible with Prof. Piccardi of University of Technology of Sidney of a large project of Surveillance funded by Australian Ministry LP0668325- “Automatic real-time detection of infiltrated objects for security of airports and train stations”.

She is author of more than 100 papers in national and international journals, and conference proceedings. She currently serve as reviewer for many international journals (e.g. IEEE Trans. on PAMI, IEEE Trans. on Circuit and Systems, Trans. on SMC, Trans. on Vehicular Technology, Trans. on Medical Imaging, Image and Vision Computing,..). She participated at scientific committees of international conferences (CVPR, ICME, ICPR, …) and symposia and organized special tracks in image processing and multimedia. She is member of GIRPR (Italy- associated with IAPR), AixIA (Ital. Assoc. Of Artificial Intelligence), ACM and IEEE Computer Society. In 2000 she organized the bi-annual School on Machine Vision of IAPR-IC. In 2005 she co-organized the 3rd Workshop of VSSN05 jointed with ACM Multimedia Conference and is currently editor of a special issue on Multimedia System Journal of ACM. In 2006 she is co-chair of the European School of Multimedia Digital Library. In 2007 she will be general chair of the 14th International Conference of Image Analysis and Processing, sponsored by IAPR.