A robust face detector algorithm utilizing neural networks and partial template matching

Pitoyo Hartono; Shuji Hashimoto

doi:10.1117/12.580586

A robust face detector algorithm utilizing neural networks and partial template matching

Pitoyo Hartono^*, Shuji Hashimoto

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	S. Kaneko, H. Cho, G.K. Knopf, R. Tutsch
Pages	119-127
Number of pages	9
Volume	5603
DOIs	https://doi.org/10.1117/12.580586
Publication status	Published - 2004
Event	Machine Vision and its Optomechatronic Applications - Philadelphia, PA, United States Duration: 2004 Oct 26 → 2004 Oct 28

Other

Other	Machine Vision and its Optomechatronic Applications
Country/Territory	United States
City	Philadelphia, PA
Period	04/10/26 → 04/10/28

Keywords

Face Detection
Neural Network
Template Matching
Voting

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

Access to Document

10.1117/12.580586

Cite this

Hartono, P & Hashimoto, S 2004, A robust face detector algorithm utilizing neural networks and partial template matching. in S Kaneko, H Cho, GK Knopf & R Tutsch (eds), Proceedings of SPIE - The International Society for Optical Engineering. vol. 5603, 16, pp. 119-127, Machine Vision and its Optomechatronic Applications, Philadelphia, PA, United States, 04/10/26. https://doi.org/10.1117/12.580586

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title = "A robust face detector algorithm utilizing neural networks and partial template matching",

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.",

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author = "Pitoyo Hartono and Shuji Hashimoto",

year = "2004",

doi = "10.1117/12.580586",

language = "English",

volume = "5603",

pages = "119--127",

editor = "S. Kaneko and H. Cho and G.K. Knopf and R. Tutsch",

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note = "Machine Vision and its Optomechatronic Applications ; Conference date: 26-10-2004 Through 28-10-2004",

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AU - Hashimoto, Shuji

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AB - 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.

KW - Face Detection

KW - Neural Network

KW - Template Matching

KW - Voting

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DO - 10.1117/12.580586

M3 - Conference contribution

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BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Kaneko, S.

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ER -

A robust face detector algorithm utilizing neural networks and partial template matching

Abstract

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Keywords

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