Learning from 1,000,000 user-uploaded faces

Authors:
Benzakhar Manashirov;Parham Aarabi
Affiliations:
ModiFace Inc., Toronto, Ontario, Canada;ModiFace Inc., Toronto, Ontario, Canada
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

Citing 3
Cited 0

Robust Real-Time Face Detection

International Journal of Computer Vision
Tiny Videos: Non-parametric Content-Based Video Retrieval and Recognition

ISM '08 Proceedings of the 2008 Tenth IEEE International Symposium on Multimedia
Real-time face detection and lip feature extraction using field-programmable gate arrays

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper combines two face detection algorithms to create a hybrid method which is more accurate and robust than either of the original methods. The face detectors are compared using a database of 1,000 user uploaded photos, which is a small subset of a much larger 1 million photo database that was generated through a popular online application that enables people to upload facial photos and to accurately locate the face in each photo.