Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
My Menu
Saved Items

FaceL: Facile Face Labeling

David S. Bolme19 Contact Information, J. Ross Beveridge19 and Bruce A. Draper19

(19)  Colorado State University, Fort Collins, CO, USA
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 .

Contact Information David S. Bolme
Email: bolme@cs.colostate.edu
Fulltext Preview (Small, Large)
Image of the first page of the fulltext

References secured to subscribers.



Export this chapter
Export this chapter as RIS | Text
 
Remote Address: 38.107.191.114 • Server: mpweb01
HTTP User Agent: CCBot/1.0 (+http://www.commoncrawl.org/bot.html)