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Embedded Hardware Face Detection
Mumbai, India January 05-January 09
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICVD.2004.126091517th International Conference on VLSI ...
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T. Theocharides, G. Link, N. Vijaykrishnan, M. J. Irwin, W. Wolf, "Embedded Hardware Face Detection," VLSI Design, International Conference on, pp. 133, 17th International Conference on VLSI Design, 2004.
 
 
BibTex
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@article{ 10.1109/ICVD.2004.1260915,
author = {T. Theocharides and G. Link and N. Vijaykrishnan and M. J. Irwin and W. Wolf},
title = {Embedded Hardware Face Detection},
journal ={VLSI Design, International Conference on},
volume = {0},
year = {2004},
issn = {1063-9667},
pages = {133},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICVD.2004.1260915},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - VLSI Design, International Conference on
TI - Embedded Hardware Face Detection
SN - 1063-9667
SP
EP
A1 - T. Theocharides,
A1 - G. Link,
A1 - N. Vijaykrishnan,
A1 - M. J. Irwin,
A1 - W. Wolf,
PY - 2004
KW - null
VL - 0
JA - VLSI Design, International Conference on
ER -
 
T. Theocharides, Pennsylvania State University
G. Link, Pennsylvania State University
N. Vijaykrishnan, Pennsylvania State University
M. J. Irwin, Pennsylvania State University
W. Wolf, Princeton University
Face detection is the first step towards face recognition and is a vital task in surveillance and security applications. Current software implementations of face detection algorithms lack the computational ability to support detection in real time video streams. Consequently, this work focuses on the design of special-purpose hardware for performing rotation invariant face detection. The synthesized design using 160nm technology is found to operate at 409.5 kHz providing a throughput of 424 frames per second and consumes 7 Watts of power. The synthesized design provided 75% accuracy in detecting faces from a set of 55 images that is competitive with existing software implementations that provide around 80-85% accuracy.
Citation:
T. Theocharides, G. Link, N. Vijaykrishnan, M. J. Irwin, W. Wolf, "Embedded Hardware Face Detection," vlsid, pp.133, 17th International Conference on VLSI Design, 2004
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