Face as an Interface


Face as an Interface
In this work, we propose a framework that enables the use of facial motion capture data as a means of user interface.
Advances in facial motion capture technology has enabled real- time, markerless facial tracking. Although originally designed to drive the motions of a virtual character, the data captured by these systems, which can be fairly extensive, could just as well be used to drive other applications. By utilizing motion capture data as user interface signals, we provide a more general means of hands-free application control, allowing for use of a wider variety of facial signals as input.
Collaborators
  • Vasudev Bethamcherla, Dept of Computer Science, Rochester Institute of Technology 
  • Nachiket Bhoyar, Dept of Computer Science, Rochester Institute of Technology 
  • Ian D’Aprix, Dept of Computer Science, Rochester Institute of Technology 
  • Ankur Doshi, Dept of Computer Science, Rochester Institute of Technology
  • Raj Paul, Dept of Computer Science, Rochester Institute of Technology
  • Siddharth Rangaishenvi, Dept of Computer Science, Rochester Institute of Technology
  • Piyush Verma, Dept of Computer Science, Rochester Institute of Technology
  • Publications
  • Vasudev Bethamcherla, Nachiket Bhoyar, Ian D'Aprix, Ankur Doshi, Raj Paul, Siddharth Rangaishenvi, Piyush Verma, and Joe Geigel. 2013. "Use of facial motion capture for hands free control of computer applications". In Proceedings of the ACM Symposium on Applied Perception (SAP '13). ACM, New York, NY, USA, 146-146.


  • Presentations
  • “Let’s Face It: Hands-Free Control Using the Face” -- ImagineRIT 2013, Rochester Institute of Technology