DocumentCode
2708938
Title
Face detection and eye localization by neural network based color segmentation
Author
Fu, Hsin-Chia ; Lai, P.S. ; Lou, P.S. ; Pao, H.T.
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Volume
2
fYear
2000
fDate
2000
Firstpage
507
Abstract
This paper presents a neural network based scheme for human face detection and eye localization in color images under an unconstrained scene. A self-growing probabilistic decision-based neural network (SPDNN) is used to learn the conditional distribution for each color classes. Pixels of a color image are first classified into facial or non-facial regions, then pixels in the facial region are followed by eye region segmentation. The class of each pixel is determined by using the conditional distribution of the chrominance components of pixels belonging to each class. The paper demonstrates a successful application of SPDNN to face detection and eye localization on a database of 755 images from 151 persons. Regarding the performance, experimental results are elaborated. As to the processing speed, the face detection and eye localization processes consume approximately 560 ms on a Pentium-II personal computer
Keywords
face recognition; feature extraction; image classification; image colour analysis; image segmentation; learning (artificial intelligence); neural nets; visual databases; Pentium-II personal computer; chrominance components; conditional distribution; experimental results; eye localization; eye region segmentation; face detection; image classification; image color segmentation; image database; learning; pixels; self-growing probabilistic decision-based neural network; Application software; Color; Face detection; Humans; Image databases; Image segmentation; Layout; Microcomputers; Neural networks; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing X, 2000. Proceedings of the 2000 IEEE Signal Processing Society Workshop
Conference_Location
Sydney, NSW
ISSN
1089-3555
Print_ISBN
0-7803-6278-0
Type
conf
DOI
10.1109/NNSP.2000.890128
Filename
890128
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