IAPR Invited Speakers

IAPR MVA2011 committee is pleased to announce the following list of invited speakers with various expertise covering 3-D modeling, augmented reality, behavior understanding and intelligent autonomous system. Audience can expect to touch the state of the arts such as medical applications, psychological applications and vehicle applications. Come and join us at MVA2011 conference!
The schedule of the invited talk will be announced subsequently.

Model Guided Multimodal Imaging and Visualization for Computer Assisted Interventions

Prof. Nassir NAVAB
Technical University of Munich

Prof. Navab

Abstract: In this talk, I will focus on the problem of design and development of advance imaging and visualization solutions for computer assisted interventions. One major scientific challenge is the recovery and modeling of surgical procedures. The second one is the analysis of large amount of heterogeneous data and their intelligent real-time fusion. The third one is the advanced visualization of such data during focused, high-intensity surgical procedures. Throughout this presentation, I use clinical applications and our recent results, obtained in our real-world laboratories within several clinics in Munich, to demonstrate the issues and to provide exemplary paths towards possible solutions. Such examples include real-time Ultrasound/CT registration, Freehand SPECT reconstruction, dynamic cone-beam reconstruction, Camera-Augmented Mobile C-arm (CAMC) and HMD based AR for intra-operative visualization and medical training.

Nassir Navab is a full professor and director of the institute for Computer Aided Medical Procedures (CAMP: http://campar.in.tum.de) at Technical University of Munich (TUM) with a secondary faculty appointment at its Medical School. In 2001, while acting as distinguished member of technical staff at Siemens Corporate Research (SCR) in Princeton, he received the prestigious Siemens Inventor of the Year Award for the body of his work in interventional imaging. He had received his PhD from INRIA and University of Paris XI and enjoyed two years postdoctoral fellowship at MIT Media Laboratory before joining SCR in 1994. In November 2006, he was elected as a member of board of directors of MICCAI society. He has been serving on the Steering Committee of the IEEE Symposium on Mixed and Augmented Reality since 2001. He is the author of hundreds of peer reviewed scientific papers and over 40 US and international patents. He is currently serving as Program Chair for MICCAI 2010 and as Area Chair for ECCV and ACCV 2010. He is on the editorial board of many international journals including IEEE TMI, MedIA and Medical Physics. He received the SMIT technology award in September 2010 and he is proud of his PhD students, who have received many prestigious awards including MICCAI young investigator awards in 2007 and in 2009, best paper award at IEEE ISMAR 2005, IBM best paper award at VOEC-ICCV 2009, IPMI Erbsmann award in 2007, AMDO best paper award in 2010.

           Behavior Imaging: Using Computer Vision to Study Autism                                                 

Prof. James M. REHG
Georgia Institute of Technology

Prof. Rehg

Abstract: In this talk I will describe current research efforts in Behavior Imaging, a new research field which encompasses the measurement, modeling, analysis, and visualization of social and communicative behaviors from multi-modal sensor data. Beginning in infancy, individuals acquire the social and communicative skills which are vital for a healthy and productive life, through face-to-face interactions with caregivers and peers. However, children with developmental delays face great challenges in acquiring these skills, resulting in substantial lifetime risks. Autism, for example, affects 1 in 110 children in the U.S. and can lead to substantial impairments, resulting in a lifetime cost of care of $3.2M per person. The goal of research in Behavior Imaging is to develop computational methods that can support the fine-grained and large-scale measurement and analysis of social behaviors, with the potential to positively impact the diagnosis and treatment of developmental disorders such as autism. A key aspect is the integration of multiple sensing modalities, including vision, speech, and wearable sensors, to obtain a comprehensive, integrated portrait of expressed behavior. In this context, machine vision technology can play a crucial role as a noninvasive means for measuring eye, face, and body movements, which can support the development of new computational models for social interactions. This talk will provide an overview of several on-going research activities, ranging from eye gaze analysis to the content-based retrieval of social games from unstructured video collections.

James M. Rehg is a Professor in the School of Interactive Computing at the Georgia Institute of Technology, where he is the Director of the Center for Behavior Imaging, co-Director of the Computational Perception Lab, and Associate Director of Research in the Center for Robotics and Intelligent Machines. He received his Ph.D. from CMU in 1995 and worked at the Cambridge Research Lab of DEC (and then Compaq) from 1995-2001, where he managed the computer vision research group. He received the National Science Foundation (NSF) CAREER award in 2001, and the Raytheon Faculty Fellowship from Georgia Tech in 2005. He and his students have received a number of best paper awards, including best student paper awards at ICML 2005 and BMVC 2010. Dr. Rehg is active in the organizing committees of the major conferences in computer vision, most-recently serving as the General co-Chair for IEEE CVPR 2009. He has served on the Editorial Board of the International Journal of Computer Vision since 2004. He has authored more than 100 peer-reviewed scientific papers and holds 23 issued US patents. Dr. Rehg is currently leading a multi-institution effort to develop the science and technology of Behavior Imaging, funded by a $10M Expedition award from the NSF (see www.cbs.gatech.edu for details).

Stereo Vision System on Automobile for Collision Avoidance

Tokyo Institute of Technology

Prof. Saneyoshi

Abstract: Several kinds of sensors such as radar, a LIDAR, an ultrasonic sensor, a monocular vision and a stereo vision to avoid a collision for automobile are on the market. To avoid a collision in the crowding traffic environment an intelligent sensor which can detect not only the distance to an obstacle but also an occupied area of the obstacle, a traffic lane, positions and motions of other cars and pedestrians and so on must be used. A stereo vision has a suitable performance because of the wide field of vision, simultaneous detection of multiple objects with size, position, relative velocity for each object as well as road shape measurement and lane marks detection on the road. But the stereo vision has several weak points: (1) an enormous amount of calculations, (2) a problem of mismatching and (3) sensitiveness to the weather condition. We have overcome these problems by many techniques such as a new hardware system for problem (1), precise rectification for (2) and proper exposure control for (3). The first our stereo vision system was presented on Tokyo Motor Show in 1991 and the performance was 10 fps with the size of 512 x 200 pixels and depth of 100 pixels. In 1999 the first stereo vision system on automobile for collision avoidance was on the market. Recently we developed a new stereo vision system which performance was 160fps with the size of 1312 x 688 pixels and depth of 176pixels. I will introduce several stereo vision systems developed up to now and these applications with a demonstration and movies.

Keiji Saneyoshi received the M.S. degree in 1977 and the Ph.D. degree in 1981, both in applied physics, from the Tokyo Institute of Technology. He was a member of the research group at Fuji Heavy Industries Ltd., before joining the Center for Biological Resources and Bioinformatics at the Tokyo Institute of Technology in 1998. He is currently an associate professor. He teaches about, and does research on, sensors and actuators for robots, especially stereo cameras and electrostatic actuators.