The nature of statistical learning theory
The nature of statistical learning theory
BEAT: the Behavior Expression Animation Toolkit
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Establishing and maintaining long-term human-computer relationships
ACM Transactions on Computer-Human Interaction (TOCHI)
A conversational agent as museum guide: design and evaluation of a real-world application
Lecture Notes in Computer Science
Interactive humanoid robots for a science museum
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
Beyond just the facts: transforming the museum learning experience
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Peg-Free Hand Shape Verification Using High Order Zernike Moments
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Empathic agents to reduce user frustration: The effects of varying agent characteristics
Interacting with Computers
Engaging constable: revealing art with new technology
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
Public displays of affect: deploying relational agents in public spaces
CHI '08 Extended Abstracts on Human Factors in Computing Systems
A virtual laboratory for studying long-term relationships between humans and virtual agents
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Relational agents improve engagement and learning in science museum visitors
IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
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Virtual agents designed to establish relationships with more than one user must be able to identify and distinguish among those users with high reliability. We describe an approach for relational agents in public spaces to identify repeat users based on two strategies: a biometric identification system based on hand geometry, and an identification dialogue that references previous conversations. The ability to re-identify visitors enables the use of persistent dialogue and relationship models, with which the agent can perform a range of behaviors to establish social bonds with users and enhance user engagement. The agent's dialogue encourages users towards repeat visits, and provides mechanisms of recovery from identification errors, as well as contextual information which may be used to improve the accuracy of the biometric identification. We have implemented and evaluated this identification system in a virtual guide agent for a science museum that is designed to conduct repeated and continuing interactions with visitors. We also present the results of a preliminary evaluation of the system, including user opinions of this technology, and of the effect of identification, both successful and unsuccessful, on acceptance and engagement of the agent.