Open AccessDisguised‐Face Discriminator for Embedded Systems
Author(s) -
Yun Woohan,
Kim DoHyung,
Yoon HoSub,
Lee Jaeyeon
Publication year - 2010
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.10.1510.0139
Subject(s) - discriminator , adaboost , boosting (machine learning) , artificial intelligence , computer science , pattern recognition (psychology) , classifier (uml) , lookup table , face detection , machine learning , facial recognition system , detector , telecommunications , programming language
In this paper, we introduce an improved adaptive boosting (AdaBoost) classifier and its application, a disguised‐face discriminator that discriminates between bare and disguised faces. The proposed classifier is based on an AdaBoost learning algorithm and regression technique. In the process, the lookup table of AdaBoost learning is utilized. The proposed method is verified on the captured images under several real environments. Experimental results and analysis show the proposed method has a higher and faster performance than other well‐known methods.