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Journal Article Disguised-Face Discriminator for Embedded Systems
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Authors
Woo-han Yun, DoHyung Kim, Ho-Sub Yoon, Jaeyeon Lee
Issue Date
2010-10
Citation
ETRI Journal, v.32, no.5, pp.761-765
ISSN
1225-6463
Publisher
한국전자통신연구원 (ETRI)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.4218/etrij.10.1510.0139
Project Code
09IC1800, Development of HRI Solutions and Core Chipsets for u-Robot, Hwang Dae Hwan
Abstract
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. © 2010 ETRI.
KSP Keywords
AdaBoost learning algorithm, Embedded system, adaptive boosting(AdaBoost), look-up table