Face image retrieval is to find from a dataset all images containing the same person in the query image. Automatic face retrieval has seen fast development in recent years, although humans still appear to be the better performer on this task. This paper reports a study towards understanding human performance on retrieving unfamiliar faces. Wild Web face images are utilized in the study, and two experiments are designed to assess human performance and behavior on the retrieval task. The experiments help to identify a set of important features and also to understand how human behaved when facing the task of retrieving unfamiliar faces. Such observations/conclusions may provide guidelines for improving existing automated algorithms.

Original languageEnglish (US)
Title of host publicationMM 2015 - Proceedings of the 2015 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Number of pages4
ISBN (Print)9781450334594
StatePublished - Oct 13 2015
Event23rd ACM International Conference on Multimedia, MM 2015 - Brisbane, Australia
Duration: Oct 26 2015Oct 30 2015


Other23rd ACM International Conference on Multimedia, MM 2015


  • Face image retrieval
  • Human performance

ASJC Scopus subject areas

  • Media Technology
  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Software


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