September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
The bigger the better – also true for action recognition?
Author Affiliations
  • Laura Fademrecht
    Max Planck Institute for Biological Cybernetics
  • Isabelle Bülthoff
    Max Planck Institute for Biological Cybernetics
  • Stephan de la Rosa
    Max Planck Institute for Biological Cybernetics
Journal of Vision August 2017, Vol.17, 987. doi:
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      Laura Fademrecht, Isabelle Bülthoff, Stephan de la Rosa; The bigger the better – also true for action recognition?. Journal of Vision 2017;17(10):987.

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      © ARVO (1962-2015); The Authors (2016-present)

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In a previous study, we have investigated action recognition performance in central vision and far visual periphery under close-to-natural conditions, i.e. using moving life-size avatars (Fademrecht, Bülthoff, and de la Rosa 2016). We found a non-linear decline of action recognition performance: recognition performance did not decline significantly up to 45° eccentricity and then declined steadily up to 60° eccentricity. To our best knowledge, such a recognition pattern has not been observed with other stimuli, like objects or faces. However, it is well known that stimulus size positively influences visual recognition performance in the visual periphery. Here, we tested recognition of life-size (30° visual angle) and small (6° visual angle) moving avatars to investigate whether the remarkably good recognition performance in the periphery was simply owed to stimulus size. We find a steeper decline of recognition performance with eccentricity for small stimuli compared to large stimuli. However, accuracy was above chance level up to 75° eccentricity for large stimuli, and up to 60° for small stimuli. These results show a surprisingly high recognition performance for human actions in the visual periphery even when the stimuli are small. Hence, bigger action stimuli are better recognized in far visual periphery, although even for small stimuli recognition performance is remarkable.

Meeting abstract presented at VSS 2017


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