A real time embedded face detector on FPGA

Kevin Irick, Theocharis Theocharides, Vijaykrishnan Narayanan, Mary Jane Irwin

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

2 Scopus citations

Abstract

Intelligent computing systems demand Human Computer Interfaces that detect and recognize the faces of human users at human interaction speeds. A real-time face detector accurately locates human faces in real-time video streams. While software implementations are effective with regards to accuracy and ease of integration, they suffer from low detection throughput on realtime video signals. In this paper we identify benefits and drawbacks of evolving face detection from software to hardware. We illustrate these tradeoffs by detailing the implementation of an Artificial Neural Network face detector on a midsize FPGA. The prototype achieves 94% detection accuracy at real-time detection rates.

Original languageEnglish (US)
Title of host publicationConference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages917-920
Number of pages4
DOIs
StatePublished - Dec 1 2006
Event40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States
Duration: Oct 29 2006Nov 1 2006

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
CountryUnited States
CityPacific Grove, CA
Period10/29/0611/1/06

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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