Purchase this article with an account.
Noa Simhi, Galit Yovel; Seeing People in Motion Enhances Person Recognition. Journal of Vision 2015;15(12):695. doi: 10.1167/15.12.695.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
The majority of studies on person recognition have examined the processing of static faces. The few studies which have examined person recognition from dynamic videos of the whole person (e.g. O'Toole et al., 2011) have done so within the same media – examining person recognition from videos after exposure to dynamic displays vs. person recognition from still images after exposure to still images alone. In this study we examined the contribution of previous exposure to motion information to whole person recognition from still images, where no dynamic information is available. To this end used a matching task in which we presented either videos of a person walking or multiple still images from the same videos and asked participants to recognize the identities shown from novel still images of either the full body, face or body alone. We found that after exposure to videos the body contributed to person recognition beyond the face; however when no dynamic information was available, person recognition from the full body was no better than person recognition from the face alone. Furthermore, we found that when less facial information was available in the videos, the body contributed more to person recognition. Finally, since person recognition from images of the body alone proved to be at chance in these experiments, we demonstrated that the inclusion of a non-informative head context alongside body only images improved person recognition, thereby suggesting that full body context is important for person recognition. Overall, these findings indicate that exposure to people in motion enhances person recognition from still images beyond person recognition based on the face alone. This suggests that body motion improves the representation of body form, thereby making the body more informative to person recognition even from still images.
Meeting abstract presented at VSS 2015
This PDF is available to Subscribers Only