ISSN 2186-7437

NII Shonan Meeting Report

No. 2013-9

First International Symposium on
Computer Behavioral Science
Atsushi Nakazawa
James Rehg
Yoichi Sato
Akihiro Sugimoto
September 26–28, 2013

National Institute of Informatics
2-1-2 Hitotsubashi, Chiyoda-Ku, Tokyo, Japan

First International Symposium on Computer
Behavioral Science
Organizers:
Atsushi Nakazawa (Kyoto University)
James Rehg (Georgia Institute of Technology)
Yoichi Sato (University of Tokyo)
Akihiro Sugimoto (National Institute of Informatics)
September 26–28, 2013

Preface
As one of the NII Shonan meetings, we organized the first international symposium on computer behavioral science, held during September 26-28, 2013. We
invited 20 researchers from Japan, United States and China, namely, 13 people
from Japan, 9 people from United States and 2 people from China.
Since the topic of this symposium is inter-disciplinary in nature, we inviteda wide variety of researchers including computer vision, ubiquitous computing,psychology, physiology, robotics and medical doctors.
In this meeting, we took a unique organization style. Each speaker wasprovided a 10-minute self-introduction slot, and we held two breakout sessions
which were used for group discussion. After the breakout sessions, we had organized sessions which summarized the respective group discussions. The meeting
was quite successful and we receive a warm reception from all participants. We
attach the following materials which is prepared / generated during the meeting.

1PeopleOrganizers
Atsushi Nakazawa (Kyoto University)
James Rehg (Georgia Institute of Technology)
Yoichi Sato (University of Tokyo)
Akihiro Sugimoto (National Institute of Informatics)
Participants
Agata Rozga (Georgia Institute of Technology)
Chun-li Yi (Peking University)
Kazuo Hiraki (University of Tokyo)
Wendy Stone (University of Washington)
Makio Kashino (NTT)Shiro Kumano (NTT)
Christian Nitschke (Kyoto University)
Jinshi Cui (Peking University)
Norimichi Ukita (NAIST)
Ikuma Adachi (Kyoto University)
Lisa Parr (Emory)
Matthew Goodwin (Northeastern Univ.)
Santosh Kumar (University of Memphis)
Kenji Suzuki (University of Tsukuba)
Daniel Messinger (University of Miami)
Tetsuya Kawahara (Kyoto University)
Kuno Yoshinori (Saitama University)
Brian Scassellati (Yale University)
Masako Myowa-Yamakoshi (Kyoto University)

2

Objective of this Symposium
Recent advances in sensors and measurement technology, including image/video
analysis, speech recognition, and wearable sensing devices, have created opportunities to measure behavior in development at an unprecedented scale andrichness. For example, eye tracking studies have illuminated the developmentof patterns of attention, and the manner in which these patterns can be disrupted by conditions such as ASD. Wearable audio recorders and associatedanalysis methods, as exemplified in the LENA system, have created new opportunities for the data-driven investigation of the emergence of language. We
believe that the confluence of sensing and computational modeling with experimental methodologies and behavioral theories will result in a new discipline,
which we term Computational Behavioral Science.
The goal of our symposium is to work together on defining this new field
and fleshing out the key research questions and issues, through a combination ofpresentations and discussions. The attendees of this meeting are drawn from awide range of disciplines, including psychology, computer science and engineering, neuroscience, and robotics. A significant number of attendees study socialand cognitive development, as well as the disruptions in development whicharise in conditions such as autism. We will use this common interest to focus
our discussion. But at the same time, we want to remain open to a broad rangeof topics and ideas at the intersection of technology and behavior.

3

Schedule
Day One09:00 – 09:15

09:15 – 09:25
09:25 – 09:35
09:35 – 09:45
09:45 – 09:55
09:55 – 10:10
10:10 – 10:20
10:20 – 10:30
10:30 – 10:40
10:40 – 10:50
10:50 – 11:00
11:00 – 11:15
11:15 – 11:25
11:25 – 11:35
11:35 – 11:45
11:45 – 11:55
11:55 – 12:05
12:15 – 13:45
13:45 – 14:00
14:00 – 15:30
15:30 – 16:00
16:00 – 17:00

Welcome address
James Rehg (Georgia Tech)
Atsushi Nakazawa (Kyoto Univ.)
Yoichi Sato (Univ. Tokyo)
Akihiro Sugimoto (Nat. Inst. of Informatics)
Self - Introductions
Agata Rozga (Georgia Tech)
Chun-li Yi (Peking Univ.)
Kazuo Hiraki (U. Tokyo)
Wendy Stone (U. Washington)
Break
Makio Kashino (NTT)Shiro Kumano (NTT)
Christian Nitschke (Kyoto Univ.)
Jinshi Cui (Peking Univ.)
Norimichi Ukita (NAIST)
Break
Ikuma Adachi (Kyoto Univ.)
Lisa Parr (Emory)
Matthew Goodwin (Northeastern Univ.)
Santosh Kumar (U. Memphis)
Kenji Suzuki (U. Tsukuba)
Lunch
Breakout Session
Organize break-out sessions
Breakout Session One
Break
Report back to group, discussion
Dinner4

Day Two
09:00 – 09:10
09:10 – 09:20
09:20 – 09:30
09:30 – 09:55
09:55 – 10:20
10:20 – 10:30
10:30 – 10:55
10:55 – 11:20
11:20 – 12:00
12:00 – 13:30
13:45 – 14:00
14:00 – 15:30
15:30 – 16:00
16:00 – 17:00

Self - Introductions
Daniel Messinger (U.Miami)
Tetsuya Kawahara (Kyoto Univ.)
Kuno Yoshinori (Saitama Univ.)
Project Presentations
Expedition in CBSJames Rehg (Georgia Tech)
Expedition in Socially Assistive Robotics
Brian Scassellati (Yale Univ.)
Break
MEXT Project, Constructive Developmental Science
Masako Myowa-Yamakoshi (Kyoto Univ.)
CREST Project, Sensing and manipulation of visual attention
Yoichi Sato (U.Tokyo) and Akihiro Sugimoto (NII)
Sign up for afternoon breakouts
Lunch
Breakout Session
Organize break-out sessions
Breakout Session Two
Break
Report back to the group, discussion
DinnerDay Three
09:00 – 09:30

09:30 – 12:00
12:00 – 1:30

Summary of Discussions
James Rehg (Georgia Tech)
Atsushi Nakazawa (Kyoto Univ.)
Yoichi Sato (Univ. Tokyo)
Akihiro Sugimoto (Nat. Inst. of Informatics)
Informal Working Group meetings
Lunch

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Presentation style
A goal of our meeting is to be able to introduce all attendees to each other inthe morning of Day One, so that we will begin to know each others interests
and research work and can work effectively as a group. To accomplish this, we
ask each attendee to prepare a Self-Introduction Talk lasting 10 minutes, described in more detail below. In addition, we will have a small number of Project
Presentations on the morning of Day Two. These presentations will describe
existing larger funded research efforts in the CBS area, and can provide additional context for our discussions. Self-Introduction Talks We ask each attendee
to prepare a 10 minute self-introduction talk. Please spend the first 5 minutesof your talk giving the audience an overview of who you are and what you workon (e.g. your appointment, educational background, research interests, etc.)
Please spend the last 5 minutes of your talk describing a single research topic or
project. Please focus on one topic only, so that you can describe it in sufficientdetail. Here are some illustrative examples: Researchers in behavior science
may want to focus on one study or finding that could provide an interesting application area for CBS. Alternatively, they may want to describe a key enabling
capability which, if they had it, would allow them to ask an interesting researchquestion. Researchers on the technology side may want to focus on a particular
project or technology that they believe may have application to the behavioral
sciences. Speakers could also spend their last 5 minutes presenting a particular
viewpoint on what CBS is or should be. In order to fit all of the 10 minutetalks into a single morning session, we will need to minimize the transition time
between talks. We will provide specific instructions prior to the meeting.

Breakout Sessions
In order to facilitate discussion among the participants, we will have two afternoons of breakout sessions. During these periods, the attendees will be divided
into small groups of 5-6 participants. Each group will discuss a particular set of
topics among themselves, and will try to reach a collective understanding about
the issues they are discussing. Each breakout group will nominate a scribe,a person in the group who will agree to take notes during the discussion andprepare a summary of the groups conclusions. The summary will take the formof a small set of powerpoint slides. After the breakout session is over, the groupwill re-assemble in the main meeting area. The scribe from each group (or analternative group member) will then give a presentation of the groups findings
to the rest of the meeting. This report-back period, in which each group reports their findings in turn, will allow all of the attendees to benefit from thediscussions in each of the groups. This organization into breakout groups willallow all of the attendees to participate in the discussion and learn from eachothers insights. We would like to structure the breakout sessions as follows: In
the first day, the breakout topics will cover a broad set of questions designed toencourage interaction between the group members and promote discussion. We
will assign participants to specific breakout groups, ensuring that each groupcontains representatives from each of the disciplines and geographic areas thatcharacterize our meeting. We hypothesize that certain themes and topics ofbroad interest to the group will emerge from these discussions. In the secondday, we will propose a wider set of more focused topics, and allow people to6choose the breakout topics which most interest them.
Breakout Session One
The goal of this first session is to start a dialog around the basic relationships
between technology and the science of behavior which define our topic of interest.
Each group will be asked to discuss the following broad sets of questions:
1. What are some key technical challenges in the measurement, modeling,
and analysis of behavior? In what areas of behavioral science has computing had the biggest impact? In what areas are computational methods theleast well-developed? What are the lowest-hanging fruit in terms of areasof behavioral study in which existing technologies could be immediately
applied?
2. What are some key constructs of social-communicative behavior that canbe addressed with a computational approach to sensing and modeling?
How can such a computational approach shed light on the link between
cognition and action? Are there new directions in experimental behavioral
research which could be enabled by anticipated advances in technology?
What are the most promising clinical applications of computational behavioral science?
We dont expect each group to address all of the questions, please feel free tochoose the subset of questions of the greatest interest to the group, or pose
alternative questions instead.
Breakout Session Two
The organizers will generate a list of discussion topics in the evening of Day One,
based on presentations and discussions during the day, and suggestions from theattendees. Attendees will have the opportunity to sign up for the sessions whichmost interest them during the morning presentation period.

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Overview of Talks
Modeling developmental trajectories in autism: Opportunities for CBS
Agata Rozga, Georgia Institute of Technology, USA
Abstract In this short talk I hope to demonstrate the advantage of a developmental approach to untangling the heterogeneity of outcomes in autism, andto demonstrate opportunities for computational behavioral science to contributeto this approach. I will illustrate this point by briefly reviewing research thatshows how children’s emerging capacity to share attention with others vis-a-vis
objects and events - joint attention - predicts language development in children
with autism.
Biography Agata Rozga is a Research Scientist in the School of Interactive Computing at Georgia Institute of Technology. She is a developmental
psychologist and an autism researcher, with a particular interest in early socialcommunicative development of children on the autism spectrum. Her current
research spans the areas of Developmental Psychology, Human-Computer Interaction, and Computational Behavioral Science, with an aim toward building
new tools to measure behaviors that are relevant both to identifying early signsof autism, and to predicting developmental trajectories and outcomes in thispopulation.

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How to help the parents understand the behaviour of autistic child
Chunli Yi, Peking University, China
Abstract ”The parents and other adults confused with autistic child, but
I found most behaviour of autistic child was reasonable, I helped the parents
understand what the child told the parents.Principle of therapy:
1. Decrease the anxiety of the parents
2. Educate the parents how to interpret the behavior, make the parents accept
the child.
3. Create the child a safe environment, which was the base of attachment
relationshipI will provide some Video to show how to capture and interpret the signal thatthe child give us.”9

Yet another approach to developmental science
Kazuo Hiraki, University of Tokyo
Abstract Progress in cognitive science requires a balance between divergence and convergence of approaches. As an interdisciplinary and integrated
field for scientific understanding of the human mind, cognitive science has incorporated diversified approaches such as computer modeling and brain imaging. These approaches brought us not only new findings but also new problems
where the findings of different approaches are sometimes in conflict with eachother. For example, the advances of infant looking-time methodologies (e.g.
Baillargeon, 1986, Ahmed and Ruffman, 1998) have led to claims that infants
know far more about the physical world than previously credited them basedon studies using more traditional methodologies (Piaget, 1954). The current
novel emphasis on electrophysiological methodologies such as EEG or ERP,
add another layer of complexity. As a result, cognitive scientists have had todevelop new models of the mind that can integrate empirical evidence acrossmultiple methodologies (e.g., Munakata, 2001) in order to converge on a unified model of cognitive functioning. In my talk, I would like to introduce yet
another approach to clarify the underlying mechanism of self-other recognitionand communication.
Biography Visiting Researcher, Birkbeck College, University of London,
2004-2005.
Associate Professor, Department of Systems Science,The University of Tokyo,
2000-2006.
Researcher, ETL(Electrotechnical Laboratory), MITI, 1993-2000.
Degrees:
Ph.D. Computer Science, Keio University, 1993.
M.S., Behavioral Science, Hokkaido University, 1989.
Research interests
Origins of Communicative Functions
Development of Cognition and Action
Brain Development
Pedagogical Machine
Machine Learning

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Early Detection of Autism: Measuring Social Gaze in Infants and Toddlers
Wendy Stone, Univ. of Washington
Abstract Early detection and intervention for children with autism canresult in dramatic gains in cognitive and behavioral skills. Because biologicalmarkers for autism have not yet been identified, diagnosis is based on behavioral
observations. Decreased social interest and attention are early-emerging behaviors that are associated with a later diagnosis of autism. However, measuringand quantifying social interest – especially eye gaze – in infants and toddlers
can present significant challenges. This presentation describes some current obstacles and promising future directions for refining the measurement of social
gaze in infants and toddlers.
Biography Dr. Wendy Stone is Professor of Psychology at the Universityof Washington. Her primary clinical and research interests are in early identification and early intervention for children with autism spectrum disorders. Her
research focuses on identifying the early-emerging behavioral features of autism,
with the goals of understanding the developmental processes that contribute to
the tremendous variability in social, learning, and behavioral outcomes for thesechildren, and implementing interventions to optimize their outcomes. She hasreceived federal funding for this research since 1993. Dr. Stone has authoredmany papers on the early identification, assessment, and follow-up of young
children with autism. Her research with young children led to the development of the Screening Tool for Autism in Two-Year-Olds (STAT) and a bookfor parents entitled, Does My Child Have Autism? She serves on the editorial
boards of Autism Research and the Journal of Autism and Developmental Disorders, and has participated in numerous work groups and review panels for
NIH and autism foundations. She is a member of the Autism Speaks Baby
Siblings Research Consortium and the Toddler Treatment Network, and serveson the Scientific Advisory Board for Autism Speaks and on the Autism Advisory Panel for Sesame Street/Sesame Workshop. Dr. Stone is committed totranslational science, and has worked to enhance knowledge and service capacity
within community settings, through training and outreach activities for families,
pediatricians, teachers, and other community professionals.

11Sensorimotor approach to autism
Makio Kashino, NTT Communication Science Laboratories
Abstract Our ongoing JST CREST project is based on the assumptionthat what we call implicit interpersonal information (IIPI), that is, interaction
or resonance of unconscious body movements or autonomic responses between
partners, should play essential roles in communication. We have been trying
to identify a set of IIPI related to the states of emotion and communication,and to reveal neural mechanisms underlying the processing of IIPI. From thisviewpoint, autism spectrum disorder (ASD) can be thought of as a set of sensorimotor impairments, which may cause problems in the processing of IIPI.
For example, we found specific deficits in basic auditory processing, which are
likely due to the malfunction of the brainstem. We are also examining motor
and autonomic properties in ASD. The sensorimotor approach to ASD would
provide objective screening methods of the disorder, promoting the transition
from symptom-based to mechanism-based diagnoses.
Biography Born in 1964. Received Ph.D. in experimental psychology
from the University of Tokyo in 2000. Joined NTT in 1989. Currently, SeniorDistinguished Scientist / Executive Manager of Human Information Science
Laboratory, NTT Communication Science Laboratories (2010-), Visiting Professor in Department of Information Processing, Tokyo Institute of Technology(2006-), and PI of JST CREST project on implicit interpersonal information(FY2010-2014). Specialized in psychophysics and systems neuroscience of auditory perception, crossmodal interaction, and communication.

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Probabilistic Modeling of Observer Perception about Empathy between Interlocutors in Multiparty Conversations
Shiro Kumano, NTT Communication Science Laboratories
Abstract In this talk, I will introduce our research framework for understanding emotions aroused between people while interacting in conversation. By
focusing on pair-wise empathy as emotional contagion, especially the process bywhich they are perceived by other people, we aim to develop a computationalmodel that realizes the automatic estimation of the perceived emotions. So far
we have proposed Bayesian modeling of the observer’s emotion perception withregard to two factors: interlocutor behavior factor and observer factor. In mypresentation, I will first explain our behavior model that relates the emotion
perceived by an anonymous observer with how interlocutors nonverbal behaviors co-occur between a pair. This model is based on our key findings that theperceptions are highly affected not only by the congruence but also by the time
lag of nonverbal behaviors between the pair. Then, I will talk about our observer
model that explains perception tendency of a specific observer from his/her gender and personality traits. We implemented this setting in the framework of aprobabilistic topic modeling.
Biography Dr. Shiro Kumano received the PhD degree in Information
Science and Technology from the University of Tokyo in 2009. He is currently
a research scientist at NTT Communication Science Laboratories. His researchinterests include computer vision, automatic meeting analysis, and affective
computing, especially in facial expression recognition and emotion estimation.
He received the ACCV 2007 Honorable Mention Award, and several awards inJapanese domestic conferences.

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Non-Intrusive Eye Gaze Tracking
Christian Nitschke, Kyoto University
Abstract It has been shown that eye gaze data can reveal important information about a persons internal state, perception and behavior. Eye gaze tracking (EGT) is, therefore, relevant for computational behavior analysis, e.g., toidentify disorder patterns. However, state-of-the-art techniques suffer from major limitations that make them impossible to be applied for meaningful tasks inreal-world situations, especially when non-experts, children, elderly and disabled
are involved. In this talk, I want to introduce our approach to non-intrusive,
flexible and practical eye gaze tracking. What makes our work different is that
we directly analyze reflected scene information at the cornea of the eye. Extracting and modeling these corneal reflections from an eye image obtains thevisual information of the environment and the relation to the observer (view,gaze). Reaching beyond current techniques, this naturally enables extension
towards tracking the complete field-of-view (peripheral vision) instead of justthe PoG.
Biography Christian Nitschke is currently an Assistant Professor at theGraduate School of Informatics, Kyoto University. He received a Diplom (M.S.)in Media Systems (Computer Science in Media) from Bauhaus Universitt Weimar,
Germany in 2006, and a Ph.D. in Engineering from Osaka University, Japan in
2011, where he continued to work as a Postdoctoral Researcher until 2013. Between 2007 and 2011 he was an R&D engineer at VIOSO GmbH, developing
solutions for multi-projector displays. Christians research interest is computerscience for visual data processing, with a focus on computer vision, computer
graphics/visualization and humancomputer interfaces. Especially, he aims inapplying corneal imaging to solve practical problems, such as non-intrusive andflexible eye gaze tracking.

14Computer vision based childrens peer play observation insocial dimension
Jinshi Cui Peking University
Abstract Childrens play with peers is often used as a context for observingsocial interaction behaviors. Free play behaviors captured by video cameras
could be processed by computer vision techniques to automatically measure theextent of social withdrawal or engagement, and it has a potential benefit for
diagnosis and assessment of autism. In this talk, I will show our preliminary
experiments on vision based play behavior analysis in social dimension. Basedon video based face pose estimation results, visual attentions are computed andplay behaviors are classified into three categories: Solitary Play, Parallel Playand Group Play. Finally, challenging issues to improve the behavior analysis
accuracy and to extend the study to autism domain will be discussed
Biography Jinshi Cui is an Associate Professor in the School Electronics
Engineering and Computer Science at Peking University (PKU), China. She
received B.E., M.E. and Ph.D. in Computer Science and Technology from Tsinghua University in 1999, 2001 and 2004 respectively. Her research interests
include computer vision (CV) and intelligent systems. She has authored over 40
papers in respected CV, robotics and ITS conferences and journals, including
CVPR, ECCV, ICRA, IROS, and T-ITS. Currently she is working on computer
vision based childrens behavior analysis in peer-play situations, together withcolleagues from psychology department of PKU.

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Wireless Physiological & Physical Activity Sensing to Enhance & Accelerate Research & Practice in Individuals with
AutismMatthew Goodwin, Northeastern University
Abstract Childrens play with peers is often used as a context for observingsocial interaction behaviors. Free play behaviors captured by video cameras
could be processed by computer vision techniques to automatically measure theextent of social withdrawal or engagement, and it has a potential benefit for
diagnosis and assessment of autism. In this talk, I will show our preliminary
experiments on vision based play behavior analysis in social dimension. Basedon video based face pose estimation results, visual attentions are computed andplay behaviors are classified into three categories: Solitary Play, Parallel Playand Group Play. Finally, challenging issues to improve the behavior analysis
accuracy and to extend the study to autism domain will be discussed
Biography Jinshi Cui is an Associate Professor in the School Electronics
Engineering and Computer Science at Peking University (PKU), China. She
received B.E., M.E. and Ph.D. in Computer Science and Technology from Tsinghua University in 1999, 2001 and 2004 respectively. Her research interests
include computer vision (CV) and intelligent systems. She has authored over 40
papers in respected CV, robotics and ITS conferences and journals, including
CVPR, ECCV, ICRA, IROS, and T-ITS. Currently she is working on computer
vision based childrens behavior analysis in peer-play situations, together withcolleagues from psychology department of PKU.

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Social Playware: Smiles of May Facilitate Social Positive
Behaviors
Kenji Suzuki, Universiy of Tsukuba
Abstract In this talk, two different wearable devices for the evidence based
practice are introduced, which enable behavior and affective measurements. We
recently reported that the specific case studies of children with autism spectrum
disorders by using the developed wearable devices, and the smiles of may facilitate social positive behaviors. The developed wearable interfaces allow us tomeasure the (i) smiles or (ii) behavior of children with ASD but also facilitate
the their social positive behaviors. Social Playware is regarded as cyber-physicalsystems to support and enhance the experiences on play and social interaction
among people by measuring and presenting physical contacts, spatial movement
and facial expression.
Biography He is currently an Associate Professor at the Center for Cybernics Research, and also the Principal Investigator of Artificial Intelligence Laboratory, University of Tsukuba, Japan. He received the B.S. degree in Physics,
M.E. and Ph.D. degrees in Pure and Applied Physics from Waseda University,
Tokyo, Japan, in 1997, 2000 and 2003, respectively. He was also a visiting researcher at the Laboratory of Physiology of Perception and Action, College deFrance, Paris in 2009, and the Laboratory of Musical Information, Universityof Genoa, Italy in 1997. His research interests include Assistive and Rehabilitation Robotics, Cognitive Robotics, Biosignal Processing, and Computational
Behavior Science.

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Emotion, Interaction, and Autism: Timing and Development
Daniel Messinger, University of Miami
Abstract Can real-time social processes illuminate developmental achievements? A dynamic systems perspective, automated measurements, and newmodeling approaches are used to understand the expression of emotion and thedevelopment of social communication in infants at risk for autism and typicallydeveloping infants.
Biography Dr. Messinger is Professor in the Department of Psychology at
the University of Miami with secondary assignments in Pediatrics and Electricaland Computer Engineering. He investigates social and emotional developmentof typically developing and at-risk infants and children. He is interested in using real-time behavioral processes to understand development, with emphases
on facial expression, adult-child interaction, and security of attachment. His
current work involves measurement of emotional dynamics, communicative development among infants at risk for autism, and the application of machinelearning approaches to infant-parent interaction. Dr, Messinger is recruiting for
doctoral and postdoctoral positions to model communication and behavior intypical and high-risk (ASD) samples as part of awards from the NIH and NSF.

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Smart Posterboard: Multi-modal Sensing and Analysis of
Poster Conversations
Tatsuya Kawahara, Kyoto University
Abstract The talk gives an overview of our project on the smart posterboard for multi-modal conversation analysis. The smart posterboard has multiple sensing devices to record poster conversations, so we can review who cameto the poster and what kind of questions or comments he/she made. The conversation analysis combines speech and image processing such as head tracking,speech enhancement and speaker diarization. Moreover, we are also investigating high-level indexing of interest and comprehension level of the audience,
based on their multi-modal behaviors during the conversation.
Biography Tatsuya Kawahara is a Professor in the Academic Center for
Computing and Media Studies and also in the School of Informatics, Kyoto University. His research interest covers speech recognition, spoken language processing, and spoken dialogue systems. He has been conducting several speech-related
projects in Japan including free large vocabulary continuous speech recognition
software (http://julius.sourceforge.jp/) and the automatic transcription system
for the Japanese Parliament (Diet).

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Developing Service Robots Based on Sociological Interaction Analysis
Yoshinori Kuno, Saitama University
Abstract We have been working toward developing service robots throughthe collaborative efforts of robotics engineers and human interaction sociologists. In our research, we first analyze human-human interaction through anexperimental, sociological approach. Second, we develop a robot system basedon the findings. Third, we evaluate human-robot interaction, again using anexperimental, sociological approach, and then modify the robot based on the
results. In this symposium, we introduce our museum guide robot, care robot,
and robotic wheelchair developed through this approach. Our museum guiderobot observes the response of visitors to its presentations, and then displays
appropriate nonverbal behaviors for attracting the visitors attention. Our carerobot detects people requesting its services, and then serves them one by one
while utilizing nonverbal behavior to display the service order. Meanwhile, ourrobotic wheelchair can move alongside a caregiver by observing his/her motion.
Biography Yoshinori Kuno received the B.S. degree, the M.S. degree,
and the Ph.D. degree in 1977, 1979, and 1982, respectively, all in electrical andelectronics engineering from the University of Tokyo . In 1982, he joined Toshiba
Corporation. From 1987 to 1988, he was a Visiting Scientist at Carnegie Mellon
University. In 1993, he moved to Osaka University as an associate professor in
the Department of Computer-Controlled Mechanical Systems. Since 2000, he
has been a professor in the Department of Information and Computer Sciences,
Saitama University.

20Socially Assistive Robotics
Brian Scassellati, Yale University
Abstract Robots have long been used to provide assistance to individual
users through physical interaction, typically by supporting direct physical rehabilitation or by providing a service such as retrieving items or cleaning floors.
Socially assistive robotics (SAR) is a comparatively new field of robotics that focuses on developing robots capable of assisting users through social rather thanphysical interaction. Just as a good coach or teacher can provide motivation,
guidance, and support without making physical contact with a student, sociallyassistive robots attempt to provide the appropriate emotional, cognitive, andsocial cues to encourage development, learning, or therapy for an individual.
In this talk, I will review some of the reasons why physical robots rather
than virtual agents are essential to this effort, highlight some of the major
research issues within this area, and describe some of our recent results building
supportive robots for teaching social skills to children with autism spectrum
disorder and for teaching nutrition to typically developing children.
Biography Brian Scassellati is a Professor of Computer Science, Cognitive
Science, and Mechanical Engineering at Yale University. His research focuses onbuilding embodied computational models of human social behavior, especiallythe developmental progression of early social skills. Using computational modeling and socially interactive robots, his research evaluates models of how infants
acquire social skills and assists in the diagnosis and quantification of disordersof social development (such as autism). His other interests include humanoid
robots, human-robot interaction, artificial intelligence, machine perception, andsocial learning.

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Development of social cognition from perinatal period: Towards new systematic understanding of its dysfunction
Masako Myowa-Yamakoshi, Kyoto University
Abstract There is a clear continuity in human sensorimotor developmentfrom prenatal to postnatal life. We have found that fetuses have some knowledge of their own bodies; they manifest a sense of knowing that their bodies
are entities different from the other entities in the external environment. However, few studies have investigated sensorimotor experience in perinatal period
might directly affect the later stage of cognitive development. In this talk, I
will present our recent findings suggesting that preterm infants and full-termneonates actually follow different trajectories in neural information processing.
Also, we will discuss the possibility that such early neural alternations in thedevelopment might be related to later difficulties with higher social-cognitive
development in preterm children.
Biography Masako Myowa-Yamakoshi received her Ph.D. from Kyoto University, Japan, in 1999. From 1997 to 2002, she was a Research Fellow of theJapan Society for the Promotion of Science, Japan. From 2003 to 2007 she
was a Senior Lecturer at the University of Shiga Prefecture. Since 2007, she
has been an Associate Professor of Kyoto University. She is the author of over
200 publications, editorials and books in the fields of Primatology and Developmental Science. She received the Nakayama Encouragement Award from the
Nakayama Foundation for Human Science, Takashima Award from the Primate
Society of Japan, and the award for International Contributions to Psychology
from the Japanese Psychological Association, among other awards. Her researchinterests include the emergence and development of human intelligence and its
evolutionary foundations.

22Sensing, predicting, and modeling human gaze
Yoichi Sato University of Tokyo
Abstract In this talk, I will give an overview of our research efforts in
JST-CREST project Sensing and controlling human gaze in daily living spacefor human-harmonized information environments. In particular, I will explain
our recent results in three directions: casual and calibration-free gaze sensing,predicting visual attention with visual saliency models, and gaze pattern analysis.
Biography Yoichi Sato is a professor at Institute of Industrial Science,
the University of Tokyo. He received his B.S. degree from the University ofTokyo in 1990, and his MS and PhD degrees in Robotics from School of Computer Science, Carnegie Mellon University in 1993 and 1997 respectively. His
research interests include physics-based vision, reflectance analysis, image-basedmodeling and rendering, and sensing and understanding of human gaze and gestures. He served/is serving to conference organization and journal editorial roles
including IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, ECCV2012 Program Co-Chair, and
IAPR MVA2013 General Chair.

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