Mobile Emotion Recognition Engine

Mobile Emotion Recognition Engine
Emotion detection within a mobile platform may be used by content developers to provide a more fulfilling user experience, such as, updating an interface and/or experience in real-time based on user emotional feedback.  The goal of this project is to create a facial expression recognition (FER) system that can accurately and efficiently process depth sensor data from a smartphone in order to elicit users’ emotional state, specifically the six Ekman emotions.

  • Alberto Scicali, Dept of Computer Science, Rochester Institute of Technology 
  • Ifeoma Nwogu, Dept of Computer Science, Rochester Institute of Technology

  • Funded by a gift from Viacom.

  • Scicali, A., I. Nwogu, and J. Geigel (2018). Mobile Facial Emotion Recognition Engine. In: ACM Symposium for Applied Perception (SAP 2018) Posters. SAP 2018. Vancouver, BC, Canada.

  • Demonstrations

  • April 28, 2018 -- Imagine RIT 2018, Rochester Institute of Technology.