FaceL: Facile Face Labeling

  • Authors:
  • David S. Bolme;J. Ross Beveridge;Bruce A. Draper

  • Affiliations:
  • Colorado State University, Fort Collins, USA;Colorado State University, Fort Collins, USA;Colorado State University, Fort Collins, USA

  • Venue:
  • ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

FaceL is a simple and fun face recognition system that labels faces in live video from an iSight camera or webcam. FaceL presents a window with a few controls and annotations displayed over the live video feed. The annotations indicate detected faces, positions of eyes, and after training, the names of enrolled people. Enrollment is video based, capturing many images per person. FaceL does a good job of distinguishing between a small set of people in fairly uncontrolled settings and incorporates a novel incremental training capability. The system is very responsive, running at over 10 frames per second on modern hardware. FaceL is open source and can be downloaded from http://pyvision.sourceforge.net/facel .