Roy A. Goode
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Roy A. Goode has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Aparna Srinath
Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
1 shared publication - Doori Lee
Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
1 shared publication - Jarrett D. Barker
Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
1 shared publication - Jason M. Gold
Department of Psychology, Indiana University, Bloomington, IN 47405, USA
1 shared publication - Jennifer L. Bittner
Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
1 shared publication - Michael Simmons
Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana, USA
1 shared publication
Latest Publications
- Open Access
- 1 April 2013
- Published by Association for Research in Vision and Ophthalmology (ARVO) in Journal of Vision
- Vol. 13 (5) , 23
The efficiency of dynamic and static facial expression recognition
Unlike frozen snapshots of facial expressions that we often see in photographs, natural facial expressions are dynamic events that unfold in a particular fashion over time. But how important are the temporal properties of expressions for our ability to reliably extract information about a person's emotional state? We addressed this question experimentally by gauging human performance in recognizing facial expressions with varying temporal properties relative to that of a statistically optimal (“ideal”) observer. We found that people recognized emotions just as efficiently when viewing them as naturally evolving dynamic events, temporally reversed events, temporally randomized events, or single images frozen in time. Our results suggest that the dynamic properties of human facial movements may play a surprisingly small role in people's ability to infer the emotional states of others from their facial expressions.
- 1 April 2013
- Published by Association for Research in Vision and Ophthalmology (ARVO) in Journal of Vision
- Vol. 13 (5) , 23
Open AccessThe efficiency of dynamic and static facial expression recognition
Unlike frozen snapshots of facial expressions that we often see in photographs, natural facial expressions are dynamic events that unfold in a particular fashion over time. But how important are the temporal properties of expressions for our ability to reliably extract information about a person's emotional state? We addressed this question experimentally by gauging human performance in recognizing facial expressions with varying temporal properties relative to that of a statistically optimal (“ideal”) observer. We found that people recognized emotions just as efficiently when viewing them as naturally evolving dynamic events, temporally reversed events, temporally randomized events, or single images frozen in time. Our results suggest that the dynamic properties of human facial movements may play a surprisingly small role in people's ability to infer the emotional states of others from their facial expressions.