Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Jin-Yul Kim"'
Publikováno v:
Journal of Korean Institute of Intelligent Systems. 32:139-144
Publikováno v:
Pattern Recognition. 132:108983
Publikováno v:
Journal of Korean Institute of Intelligent Systems. 28:321-327
Publikováno v:
The Transactions of The Korean Institute of Electrical Engineers. 66:682-691
Publikováno v:
The Transactions of The Korean Institute of Electrical Engineers. 66:672-681
This paper is concerned with the design methodology of face recognition system based on pose estimation. In 2-dimensional face recognition, the variations of facial pose cause the deterioration of recognition performance because object recognition is
Publikováno v:
Journal of Korean Institute of Intelligent Systems. 26:259-266
Publikováno v:
Journal of Korean Institute of Intelligent Systems. 26:120-126
In this study, we propose a method for effectively detecting and recognizing the face in image using RBFNNs pattern classifier and HCbCr-based skin color feature. Skin color detection is computationally rapid and is robust to pattern variation for fa
Publikováno v:
Journal of Korean Institute of Intelligent Systems. 26:56-63
In this study, we introduce a design of Fuzzy RBFNNs-based digi t recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Com ponent Analysis (PCA) is a widely-adopted dimen-sional reduction algorithm,
Autor:
Jin-Yul Kim, Jae-Ki Jeong
Publikováno v:
The Journal of Korean Institute of Communications and Information Sciences. 40:2090-2101
We propose a robust tracking method that combines the merits of ACM(active contour model) and the color-based PF(particle filter), effectively. In the proposed method, PF and ACM track the color distribution and the contour of the target, respectivel
Publikováno v:
The Transactions of The Korean Institute of Electrical Engineers. 64:1347-1355
In this study, we compare the recognition performance using PCA and RBFNNs for introducing robust face recognition system to pose variations based on pose estimation. proposed face recognition system uses Honda/UCSD database for comparing recognition