Artificial Neural Network architectures for human face detection

Mark Propp, Ashok K Samal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Humans detect and identify faces in a scene with little or no effort. However, building an automated system that accomplishes this task has proven to be very difficult. A robust automated system for face recognition would find many applications, such as criminal identification, and authentication in secure systems. This paper describes a system based on artificial neural nets that is capable of detecting a face from an arbitrary image in a robust manner. The system correctly classified 91% of the face images and 88% of the non-face images.

Original languageEnglish (US)
Title of host publicationIntelligent Engineering Systems Through Artificial Neural Networks
EditorsC.H. Dagli, L.I. Burke, Y.C. Shin
Place of PublicationFairfield, NJ, United States
PublisherASME
Pages535-540
Number of pages6
Volume2
Publication statusPublished - 1992
EventProceedings of the 1992 Artificial Neural Networks in Engineering, ANNIE'92 - St.Louis, MO, USA
Duration: Nov 15 1992Nov 18 1992

Other

OtherProceedings of the 1992 Artificial Neural Networks in Engineering, ANNIE'92
CitySt.Louis, MO, USA
Period11/15/9211/18/92

    Fingerprint

ASJC Scopus subject areas

  • Software

Cite this

Propp, M., & Samal, A. K. (1992). Artificial Neural Network architectures for human face detection. In C. H. Dagli, L. I. Burke, & Y. C. Shin (Eds.), Intelligent Engineering Systems Through Artificial Neural Networks (Vol. 2, pp. 535-540). Fairfield, NJ, United States: ASME.