GFT Facial Expression Database

Contributors:
  1. Wen-Sheng Chu
  2. Fernando De la Torre
  3. Michael A Sayette

Date created: | Last Updated:

: DOI | ARK

Category: Data

Description: Despite the important role that facial expressions play in interpersonal communication and our knowledge that interpersonal behavior is influenced by social context, no currently available facial expression database includes multiple interacting participants. The Sayette Group Formation Task (GFT) database addresses the need for well-annotated video of multiple participants during unscripted interactions. The database includes 172,800 video frames from 96 participants in 32 three-person groups. To aid in the development of automated facial expression analysis systems, GFT includes expert annotations of FACS occurrence and intensity, facial landmark tracking, and baseline results for linear SVM, deep learning, active patch learning, and personalized classification. Baseline performance is quantified and compared using identical partitioning and a variety of metrics (including means and confidence intervals). The highest performance scores were found for the deep learning and active patch learning methods. Learn more at http://osf.io/7wcyz.

License: CC-By Attribution 4.0 International

Has supplemental materials for GFT Facial Expression Database on PsyArXiv

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GFT Facial Expression Database The Sayette Group Formation Task (GFT) Spontaneous Facial Expression Database has two components: meta-data and video data. Because video, by its very nature, reveals person identity, a separate procedure is needed for its distribution. The video data is available from the University of Pittsburgh using the procedures described below. The meta-data is available on th...

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