Face detection and eye localization by neural network based color segmentation

Hsin Chia Fu*, P. S. Lai, R. S. Lou, Hsiao-Tien Pao

*Corresponding author for this work

Research output: Contribution to conferencePaper

8 Scopus citations

Abstract

This paper presents a neural network based scheme for human face detection and eye localization in color images under non-constrained 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 in Section 3. As to the processing speed, the face detection and eye localization processes consume approximately 560 ms on a Pentium-II personal computer.

Original languageEnglish
Pages507-516
Number of pages10
StatePublished - 1 Dec 2000
Event10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000) - Sydney, Australia
Duration: 11 Dec 200013 Dec 2000

Conference

Conference10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000)
CitySydney, Australia
Period11/12/0013/12/00

Fingerprint Dive into the research topics of 'Face detection and eye localization by neural network based color segmentation'. Together they form a unique fingerprint.

  • Cite this

    Fu, H. C., Lai, P. S., Lou, R. S., & Pao, H-T. (2000). Face detection and eye localization by neural network based color segmentation. 507-516. Paper presented at 10th IEEE Workshop on Neural Network for Signal Processing (NNSP2000), Sydney, Australia, .