Dissecting the time course of person recognition in natural viewing environments

Abstract

Person recognition often unfolds over time and distance as a person approaches, with the quality of identity information from faces, bodies, and motion in constant flux. Participants were familiarized with identities using close‐up and distant videos. Recognition was tested with videos of people approaching from a distance. We varied the timing of prompted responses in the test videos, the amount of video seen, and whether the face, body, or whole person was visible. A free response condition was also included to allow participants to respond when they felt ‘confident’. The pattern of accuracy across conditions indicated that recognition judgments were based on the most recently available information, with no contribution from qualitatively diverse and statistically useful person cues available earlier in the video. Body recognition was stable across viewing distance, whereas face recognition improved with proximity. The body made an independent contribution to recognition only at the farthest distance tested. Free response latencies indicated meta‐knowledge of the optimal proximity for recognition from faces versus bodies. Notably, response bias varied strongly as a function of participants’ expectation about whether closer proximity video was forthcoming. These findings lay the groundwork for developing person recognition theories that generalize to natural viewing environments.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 09, 2015
Source ID
10.1111/bjop.12125

Entities

People

  • Alice J. O'toole
  • Carina A. Hahn
  • P Jonathon Phillips

Organizations

  • National Institute of Standards and Technology
  • United States Department of Defense
  • University of Texas at Dallas

Tags

Fields of Study

  • Psychology

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Image Processing and Computer Vision.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference