BP4D: 4D Spontaneous Facial Expression Database

 Background: 

Because posed and un-posed (aka “spontaneous”) 3D facial expressions differ along several dimensions including complexity and timing, well-annotated 3D video of un-posed facial behavior is needed. The BP4D dataset comprises videos of spontaneous facial expressions in a diverse group of young adults. Well-validated emotion inductions were used to elicit expressions of emotion and paralinguistic communication. Frame-level ground-truth for facial actions was obtained using the Facial Action Coding System. Facial features were tracked in both 2D and 3D domains using both person-specific and generic approaches. The work promotes the exploration of 3D spatiotemporal features in subtle facial expression, better understanding of the relation between pose and motion dynamics in facial action units, and deeper understanding of naturally occurring facial action.

 Technology Overview: 

  The database includes data from 41 participants (23 women, 18 men): 18 – 29 years of age; 11 Asian, 6 Black, 4 Hispanic, and 20 White.  An emotion elicitation protocol was designed to elicit emotions of participants effectively. Eight tasks were covered with an interview process and a series of activities to elicit eight emotions.    The database is structured by participants. Each participant is associated with 8 tasks. For each task, there are both 3D and 2D videos. The Metadata include manually annotated action units (FACS AU), automatically tracked head pose, and 2D/3D facial landmarks.  The database is in the size of about 2.6TB (without compression).   Xing Zhang, Lijun Yin, Jeff Cohn, Shaun Canavan, Michael Reale, Andy Horowitz, Peng Liu, and Jeff Girard, “BP4D-Spontaneous: A high resolution spontaneous 3D dynamic facial expression database”, Image and Vision Computing, 32 (2014), pp. 692-706  (special issue of the Best of FG13)   Xing Zhang, Lijun Yin, Jeff Cohn, Shaun Canavan, Michael Reale, Andy Horowitz, and Peng Liu, “A high resolution spontaneous 3D dynamic facial expression database”, The 10^th IEEE International Conference on Automatic Face and Gesture Recognition (FG13),  April, 2013.