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Proceedings Paper

A robust face detector algorithm utilizing neural networks and partial template matching
Author(s): Pitoyo Hartono; Shuji Hashimoto
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Paper Abstract

Face detection from an arbitrary scene has become a very actively studied topic in the image processing and pattern recognition fields. The reason for the importance of face detection is in its broad applications, for example in human detection by means of visual input for security reason, human-machine interaction, and video archiving. Human face is composed from several components, each with large varieties and it can take many postures in arbitrary scene, which make detection task a very difficult one. In this study we propose a method for robust face detection from arbitrary scene utilizing neural network as face's posture predictor and partial template matching of human face. The proposed model is robust to the lighting conditions and postures of the frontal faces.

Paper Details

Date Published: 25 October 2004
PDF: 9 pages
Proc. SPIE 5603, Machine Vision and its Optomechatronic Applications, (25 October 2004); doi: 10.1117/12.580586
Show Author Affiliations
Pitoyo Hartono, Waseda Univ. (Japan)
Shuji Hashimoto, Waseda Univ. (Japan)


Published in SPIE Proceedings Vol. 5603:
Machine Vision and its Optomechatronic Applications
Shun'ichi Kaneko; Hyungsuck Cho; George K. Knopf; Rainer Tutsch, Editor(s)

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