Glasses Detection by Boosting Simple Wavelet Features

Authors:
Bo Wu;Haizhou Ai;Ran Liu
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;Tsinghua University, Beijing, China
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Year:
2004

Citing 0
Cited 2

Face description for perceptual user interfaces

CAEPIA'05 Proceedings of the 11th Spanish association conference on Current Topics in Artificial Intelligence
An analysis of facial description in static images and video streams

IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose a novel method for glasses detection. The glasses detectors are learned by using a variation of boosting algorithm, called real Adaboost [Improved Boosting Algorithms Using Confidence-rated Predictions], to boost simple wavelet feature based Look-Up-Table type weak classifiers. Two types of wavelet features, Haar and Gabor, have been investigated. Experiments results are reported to show that our method has very high correctness and extremely fast running speed. Based on this method we have developed a glasses detection system which can detect the glasses in facial images automatically.