More human than human?: a visual processing approach to exploring believability of android faces

More human than human?: a visual processing approach to exploring believability of android faces More Human than Human? A Visual Processing Approach to Exploring Believability of Android Faces Masayuki Nakane University of Manitoba umnakane@myumanitoba.ca ABSTRACT James E. Young University of Manitoba young@cs.umanitoba.ca Neil D. B. Bruce University of Manitoba bruce@cs.umanitoba.ca The issue of believability is core to android science, the challenge of creating a robot that can pass as a near human. While researchers are making great strides in improving the quality of androids and their likeness to people, it is simultaneously important to develop theoretical foundations behind believability, and experimental methods for exploring believability. In this paper, we explore a visual processing approach to investigating the believability of android faces, and present results from a study comparing current-generation android faces to humans. We show how android faces are still not quite as believable as humans, and provide some mechanisms that may be used to investigate and compare believability in future projects. Author Keywords In this paper, we take an initial step toward this goal by exploring visual perception and processing of android faces. We purposely select a heavy simplification of the broader problem, focusing on the visual perception of static images of android faces. This serves as an initial base case http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

More human than human?: a visual processing approach to exploring believability of android faces

Association for Computing Machinery — Oct 29, 2014

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Datasource
Association for Computing Machinery
Copyright
Copyright © 2014 by ACM Inc.
ISBN
978-1-4503-3035-0
D.O.I.
10.1145/2658861.2658893
Publisher site
See Article on Publisher Site

Abstract

More Human than Human? A Visual Processing Approach to Exploring Believability of Android Faces Masayuki Nakane University of Manitoba umnakane@myumanitoba.ca ABSTRACT James E. Young University of Manitoba young@cs.umanitoba.ca Neil D. B. Bruce University of Manitoba bruce@cs.umanitoba.ca The issue of believability is core to android science, the challenge of creating a robot that can pass as a near human. While researchers are making great strides in improving the quality of androids and their likeness to people, it is simultaneously important to develop theoretical foundations behind believability, and experimental methods for exploring believability. In this paper, we explore a visual processing approach to investigating the believability of android faces, and present results from a study comparing current-generation android faces to humans. We show how android faces are still not quite as believable as humans, and provide some mechanisms that may be used to investigate and compare believability in future projects. Author Keywords In this paper, we take an initial step toward this goal by exploring visual perception and processing of android faces. We purposely select a heavy simplification of the broader problem, focusing on the visual perception of static images of android faces. This serves as an initial base case

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