ICIMCS2011 Keynotes
Keynote 1: Social Life Networks

Ramesh Jain, Department of Computer Science, University of California, Irvine CA, USA

Abstract: We are living in an age of social media that provides numerous channels for digital expression and sharing almost instantaneously in any part of the world. By bringing different media as well as modes of distribution -- focused, narrowcast, and broadcast -- social networks (SN) have revolutionized communication among people. We believe that by using the enormous reach of mobile phones equipped with myriads of sensors, the next generation of social networks can be designed not only to connect people with other people, but also to connect people with other people and essential life resources. We call these networks Social Life Networks (SLN) and believe that this is the right time to focus efforts to discover and develop technology and infrastructure to design and build these networks.  We will discuss our efforts in building SLNs and identify challenges that must be addressed to make them practical.

BiographyRamesh Jain is an entrepreneur, researcher, and educator.

Ramesh co-founded several companies, managed them in initial stages, and then turned them over to professional management.  These companies include PRAJA, Virage, and ImageWare.  Currently he is involved in two new start-ups as cofounder and advisor: mChron and Stikco Studio.  He has also been advisor to several other companies including some of the largest companies in media and search space.

He is a Donald Bren Professor in Information & Computer Sciences at University of California, Irvine where he is doing research in Event Web and experiential computing.  Earlier he served on faculty of Georgia Tech, University of California at San Diego, The university of Michigan, Ann Arbor, Wayne State University, and Indian Institute of Technology, Kharagpur.  He is a Fellow of ACM, IEEE, AAAI, IAPR, and SPIE.  His current research interests are in searching multimedia data and creating EventWebs for experiential computing.  He is the recipient of several awards including the ACM SIGMM Technical Achievement Award 2010.

Keynote 2: Social Media Mining: from Recommendation to Prediction and Forecast

Jiebo Luo, Kodak Research Labs

Abstract: Increasingly rich and large-scale social media data (including texts, images, audios, videos) are being posted to social networking and media sharing websites. Researchers from multidisciplinary areas are developing methods for processing social media and employing such rich multi-modality data for various applications. We present a few recent advances in this nascent area. First, to expand one鈥檚 social network through media sharing, we have developed novel methods to produce accurate suggestions of suitable social groups from a user's personal photo collection. Both visual content and textual annotations are integrated to generate initial predictions of the group categories for the images. The strong relationship among images in a user's collection is modeled as a sparse graph and a collection-based sparse label propagation method is further proposed to improve the group suggestions. Second, we explore the global trends and sentiments that can be drawn by analyzing the sharing patterns of uploaded and downloaded social multimedia. We consider that each time an image or video is uploaded or shared, it constitutes an implicit yet trustworthy vote for (or against) the subject of the image. By aggregating such votes across millions of Internet users, we reveal the wisdom that is embedded in social multimedia sites for social science applications such as politics, economics, and marketing.

BiographyJiebo Luo is a Senior Principal Scientist with the    Kodak Research Laboratories in Rochester, NY. His research interests include image processing, computer vision, machine learning, and the related multi-disciplines such as multimedia data mining, medical imaging, and computational photography. Dr. Luo has authored over 160 technical papers and holds over 60 US patents. Dr. Luo has been actively involved in numerous technical conferences, including serving as the general chair of ACM CIVR 2008, program co-chair of IEEE CVPR 2012, ACM Multimedia 2010 and SPIE VCIP 2007, area chair of IEEE ICASSP 2009-2011, ICIP 2008-2011, CVPR 2008 and ICCV 2011, and an organizer of ICME 2006/2008/2010 and ICIP 2002. Currently, he serves on several IEEE SPS Technical Committees (IMDSP, MMSP, and MLSP) and conference steering committees (ACM ICMR and IEEE ICME). He is the Editor-in-Chief of the Journal of Multimedia, and has served on the editorial boards of the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), the IEEE Transactions on Multimedia (TMM), the IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), Pattern Recognition (PR), Machine Vision and Applications (MVA), and Journal of Electronic Imaging (JEI). He is a Fellow of the SPIE, IEEE, and IAPR.

Keynote 3: Microsoft Kinect Sensor and Natural User Interaction

Zhengyou Zhang, Microsoft Research, Redmond, USA

Abstract: Recent advances in 3D depth cameras such Microsoft Kinect sensors have created many opportunities towards a more natural way of interacting with computers and with people across distances. Microsoft Kinect allows Xbox 360 to directly sense the 3rd dimension (depth) of the players and the environment, and revolutionizes the experience how a player interacts with the games (“you are the controller”). However, its impact is way beyond the gaming industry. With its readily availability and low cost, many researchers and practitioners in computer science, electronic engineering and robotics are leveraging the sensing technology to develop new ways of interacting with machines. Natural user interaction is around the corner. In this talk, I will describe the principles behind the Kinect sensing technology and some of its applications including person tracking, avatar animation and action recognition.

BiographyZhengyou Zhang is is a Principal Researcher with Microsoft Research, Redmond, WA, USA, and manages the multimodal collaboration research team. Before joining Microsoft Research in March 1998, he was with INRIA (French National Institute for Research in Computer Science and Control), France, for 11 years and was a Senior Research Scientist from 1991. In 1996-1997, he spent a one-year sabbatical as an Invited Researcher with the Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan. He has published over 200 papers in refereed international journals and conferences, and has coauthored the following books: 3-D Dynamic Scene Analysis: A Stereo Based Approach (Springer-Verlag, 1992); Epipolar Geometry in Stereo, Motion and Object Recognition (Kluwer, 1996); Computer Vision (Chinese Academy of Sciences, 1998, 2003, in Chinese); Face Detection and Adaptation (Morgan and Claypool, 2010), and Face Geometry and Appearance Modeling (Cambridge University Press, 2011). He has given a number of keynotes in international conferences.

Dr. Zhang is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE), the Founding Editor-in-Chief of the IEEE Transactions on Autonomous Mental Development, an Associate Editor of the International Journal of Computer Vision, and an Associate Editor of Machine Vision and Applications. He served as Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence from 2000 to 2004, an Associate Editor of the IEEE Transactions on Multimedia from 2004 to 2009, among others. He has been on the program committees for numerous international conferences in the areas of autonomous mental development, computer vision, signal processing, multimedia, and human-computer interaction. He served as a Program Co-Chair of the International Conference on Multimedia and Expo (ICME), July 2010, a Program Co-Chair of the ACM International Conference on Multimedia (ACM MM), October 2010, and a Program Co-Chair of the ACM International Conference on Multimodal Interfaces (ICMI), November 2010. He is serving a General Co-Chair of the IEEE International Workshop on Multimedia Signal Processing (MMSP), October 2011.