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Keynote Speakers



Tuesday, March 22, 8:30am

Jamie Shotton, Microsoft Research Cambridge

Title: Body Part Recognition: Making Kinect Robust

Abstract: Last November, Microsoft launched Kinect for Xbox 360 (http://www.xbox.com/kinect), a revolution in gaming where your whole body becomes the controller - you need not hold any device or wear anything special. Human pose estimation has long been a “grand challenge” of computer vision, and Kinect is the first product that meets the speed, cost, accuracy, and robustness requirements to take pose estimation out of the lab and into the living room. In the first two months since launch it has sold over 8 million units. In this talk we will discuss some of the technology behind Kinect, detailing our new approach which forms one of the core algorithms inside Kinect: body part recognition. Deriving from our earlier work that uses machine learning to recognize categories of objects in photographs, body part recognition uses a classifier to produce an interpretation of pixels coming from the Kinect depth-sensing camera into different parts of the body: head, left hand, right knee, etc. Estimating this pixel-wise classification is extremely efficient, as each pixel can be processed independently on the GPU. The classifications can then be pooled across pixels to produce hypotheses of 3D body joint positions for use by a skeletal tracking algorithm. We designed the system to be robust, in two ways in particular. Firstly, we train the system on a powerful cluster from a vast and highly varied training set of synthetic images to ensure the system works for all ages, body shapes & sizes, clothing and hair styles. Secondly, the recognition does not rely on any temporal information, ensuring that the system can initialize from arbitrary poses and preventing catastrophic loss of track, enabling extended gameplay for the first time.

Bio: Jamie Shotton studied Computer Science at the University of Cambridge, and remained at Cambridge for his PhD in Computer Vision and Visual Object Recognition, graduating in 2007.  He was awarded the Toshiba Fellowship and travelled to Japan to continue his research at the Toshiba Corporate Research & Development Center in Kawasaki.  In 2008 he returned to the UK and started work at Microsoft Research Cambridge where he is a Researcher in the Machine Learning & Perception group.

His research interests include Object Recognition, Machine Learning, Human Pose Estimation, Gesture and Action Recognition, and Medical Imaging.   He has published papers in all the major computer vision conferences and journals, with a focus on object detection by modelling contours, semantic scene segmentation exploiting both appearance and semantic context, and dense object part layout constraints.  His demo on real-time semantic scene segmentation won the best demo award at CVPR 2008.  More recently, he has investigated how many of the ideas from visual object recognition and machine learning can be applied in new ways.  In human pose estimation, he architected the human body part recognition algorithm that drives Xbox Kinect’s skeletal tracking algorithm.  In the sphere of medical imaging, he has published papers on the automatic recognition of organs and other anatomical structures from CT data, with a view to simplifying and speeding up the radiologist’s workflow.

More information is available here: http://research.microsoft.com/en-US/people/jamiesho/default.aspx



Wednesday, March 23, 8:30am

Brad Duchaine, Dartmouth College

Title: Exploring human social perception via deficits and disruptions

Abstract: I will discuss findings from studies involving developmental prosopagnosics, acquired prosopagnosics, and transcranial magnetic stimulation that shed light on the organization of face processing, body processing, and visual recognition more generally.

Bio: Brad Duchaine is an associate professor in the Department Psychological and Brain Science at Dartmouth College. His research uses neuropsychology, psychophysics, neuroimaging, twin studies, and transcranial magnetic stimulation to explore social perception. Brad received his PhD in Psychology at UC-Santa Barbara in 2001, worked as a postdoctoral fellow in Harvard's Vision Sciences Lab until 2005, and served as a group leader at the Institute of Cognitive Neuroscience at University College London from 2005-2010.



Thursday, March 24, 3:10pm

Jonathan Gratch, USC

Title: So she's smiling, now what?

Abstract: Face and gesture research has made enormous progress in recognizing human nonverbal signals, but still faces important challenges in understanding the social meaning and significance of such cues. In this talk I will discuss a number of successes and some failures in using expression and gesture recognition techniques in a variety of human-human and human-computer social contexts. On the one hand, I will describe research on virtual humans (interactive digital characters) that can engage users in rich face-to-face interactions. I will describe evidence that endowing these artifacts with the ability to recognize and respond to human nonverbal cues has important social effects such as enhanced mutual understanding and persuasiveness. On the other hand, by facilitating the annotation of human nonverbal behavior, face and gesture research is revolutionizing the study of human social processes and providing new insights into theories of human social behavior. These two topics work hand-in-hand, as theories of human social processes have important implications, not only for the design of interactive virtual humans, but for face and gesture research as well. I will end by describing how social psychological theory, especially theories of emotion, has implications for research in the automatic recognition and understanding of human social signals.

Bio: Jonathan Gratch is an Associate Director for Virtual Humans Research at the University of Southern California's (USC) Institute for Creative Technologies, Research Associate Professor in the Department of Computer Science and co-director of USC's Computational Emotion Group. He completed his Ph.D. in Computer Science at the University of Illinois in Urban-Champaign in 1995. Dr. Gratch's research focuses on computational models of human social processes, especially emotion, and explores these models' role in shaping human-computer interactions in virtual environments. He studies the relationship between cognition and emotion, the cognitive processes underlying emotional responses, and the influence of emotion on decision making and physical behavior. His research has been supported by the National Science Foundation, AFOSR, DARPA and RDECOM. He currently serves as the Editor-in-Chief of IEEE's Transactions on Affective Computing, Associate Editor of Emotion Review and the Journal of Autonomous Agents and Multiagent Systems, President of the HUMAINE Association, the international society for research on emotion and human-computer interaction, and is a member of IEEE, the Association for the Advancement of Artificial Intelligence (AAAI) and the International Society for Research on Emotion (ISRE). Dr. Gratch is the author of over 150 technical articles.

Latest News at FG

   

FG 2011 was a success, with great keynote talks, an excellent program of presentations, posters, demos, and exhibits, as well as five workshops and three tutorials. Thanks to everyone whose efforts made the conference possible!

The proceedings will be available at IEEE Xplore in the near future. The location and organizers of FG 2013 will be announced here soon.


Registration hours

*Weather Update* - The weather forecast for the week of FG is not good - rainy and relatively cool. Bring an umbrella if you can!

Santa Barbara weather - 5-day forecast

No health risk to California from radiation

UCSB Allosphere tour

All conference presenters: please see the Information for Presenters.

The final program is available for the main conference.

Tutorials will be presented at FG 2011 on Monday and Friday. See the list and schedule of tutorials and workshops.

Scheduled keynote speakers