Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41216

Interactive Realistic Digital Avatars - Revisiting the Uncanny Valley

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Title: Interactive Realistic Digital Avatars - Revisiting the Uncanny Valley
Authors: Seymour, Michael
Riemer, Kai
Kay, Judy
Keywords: Avatar
Embodied Conversation Agents
Interactive
Uncanny Valley
Issue Date: 04 Jan 2017
Abstract: The 40-year-old Uncanny Valley theory is influential in the discussion surrounding acceptance of realistic graphical agents. This theory was formulated by observing robots. While it has been shown to be valid when observing digital characters, little has been studied about acceptance when people interact with avatars, rather than simply observe a recording. \ \ The emerging technology that will soon be able to create realistic avatars challenges the conventional view built on this theory, that affinity is a function of ‘appearance’, necessitating a reevaluation of the dimensions of the problem. We introduce a broader theoretical foundation with an additional dimension, namely interactivity. \ \ Studies that have validated the Uncanny Valley used still images or clips from existing media, but did not explore interactivity. In this study we suggest that interactivity operates on an independent, orthogonal dimension to ‘appearance’, and that interaction can ‘overcome the valley’ in affinity due to matching and common human non-verbal cues. We hypothesize that these cause the user to process the avatar differently. We contribute to the literature a new way to theorize the relationship between avatar realism and affinity, including both avatar appearance and interaction, and outline a research design to study this relationship. \
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41216
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.067
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Human-Computer Interaction: Informing Design Utilizing Behavioral, Neurophysiological, and Design Science Methods Minitrack



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