Real-Time multiple face detection of pedestrian using hybrid GA

Hidekazu Suzuki, Mamoru Minami

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

Abstract

There have been many attempts to realize human-like visual function by image processing. Methods for recognition and tracking of the human face are expected to be applied in security systems and in the field of ITS (Intelligent Transportation Systems). This study was performed to construct a detection system capable of recognizing multiple people's faces in real time. We employed a hybrid GA (Genetic Algorithm) based on selective attention, which is the human visual function used to reduce processing load, to search for the position of a face in input images. The hybrid GA used random searching as a rough, preliminary search of the area, then used an improved GA to carefully search the target possibilities. These methods were combined by grouping to allow simultaneous detection of multiple faces in input images in real time. We confirmed the effectiveness of our proposed detection system by experiments involving detection of multiple targets.

Original languageEnglish
Title of host publicationIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Pages708-713
Number of pages6
Publication statusPublished - 2004
Externally publishedYes
EventProceedings - 7th International IEEE Conference on Intelligent Transportation Systems, ITSC 2004 - Washington, DC, United States
Duration: Oct 3 2004Oct 6 2004

Other

OtherProceedings - 7th International IEEE Conference on Intelligent Transportation Systems, ITSC 2004
CountryUnited States
CityWashington, DC
Period10/3/0410/6/04

Fingerprint

Face recognition
Genetic algorithms
Security systems
Image processing
Processing
Experiments

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Suzuki, H., & Minami, M. (2004). Real-Time multiple face detection of pedestrian using hybrid GA. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 708-713)

Real-Time multiple face detection of pedestrian using hybrid GA. / Suzuki, Hidekazu; Minami, Mamoru.

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 2004. p. 708-713.

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

Suzuki, H & Minami, M 2004, Real-Time multiple face detection of pedestrian using hybrid GA. in IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. pp. 708-713, Proceedings - 7th International IEEE Conference on Intelligent Transportation Systems, ITSC 2004, Washington, DC, United States, 10/3/04.
Suzuki H, Minami M. Real-Time multiple face detection of pedestrian using hybrid GA. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 2004. p. 708-713
Suzuki, Hidekazu ; Minami, Mamoru. / Real-Time multiple face detection of pedestrian using hybrid GA. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 2004. pp. 708-713
@inproceedings{54eaaecaa29740a5bd93dbd2af9b229d,
title = "Real-Time multiple face detection of pedestrian using hybrid GA",
abstract = "There have been many attempts to realize human-like visual function by image processing. Methods for recognition and tracking of the human face are expected to be applied in security systems and in the field of ITS (Intelligent Transportation Systems). This study was performed to construct a detection system capable of recognizing multiple people's faces in real time. We employed a hybrid GA (Genetic Algorithm) based on selective attention, which is the human visual function used to reduce processing load, to search for the position of a face in input images. The hybrid GA used random searching as a rough, preliminary search of the area, then used an improved GA to carefully search the target possibilities. These methods were combined by grouping to allow simultaneous detection of multiple faces in input images in real time. We confirmed the effectiveness of our proposed detection system by experiments involving detection of multiple targets.",
author = "Hidekazu Suzuki and Mamoru Minami",
year = "2004",
language = "English",
pages = "708--713",
booktitle = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",

}

TY - GEN

T1 - Real-Time multiple face detection of pedestrian using hybrid GA

AU - Suzuki, Hidekazu

AU - Minami, Mamoru

PY - 2004

Y1 - 2004

N2 - There have been many attempts to realize human-like visual function by image processing. Methods for recognition and tracking of the human face are expected to be applied in security systems and in the field of ITS (Intelligent Transportation Systems). This study was performed to construct a detection system capable of recognizing multiple people's faces in real time. We employed a hybrid GA (Genetic Algorithm) based on selective attention, which is the human visual function used to reduce processing load, to search for the position of a face in input images. The hybrid GA used random searching as a rough, preliminary search of the area, then used an improved GA to carefully search the target possibilities. These methods were combined by grouping to allow simultaneous detection of multiple faces in input images in real time. We confirmed the effectiveness of our proposed detection system by experiments involving detection of multiple targets.

AB - There have been many attempts to realize human-like visual function by image processing. Methods for recognition and tracking of the human face are expected to be applied in security systems and in the field of ITS (Intelligent Transportation Systems). This study was performed to construct a detection system capable of recognizing multiple people's faces in real time. We employed a hybrid GA (Genetic Algorithm) based on selective attention, which is the human visual function used to reduce processing load, to search for the position of a face in input images. The hybrid GA used random searching as a rough, preliminary search of the area, then used an improved GA to carefully search the target possibilities. These methods were combined by grouping to allow simultaneous detection of multiple faces in input images in real time. We confirmed the effectiveness of our proposed detection system by experiments involving detection of multiple targets.

UR - http://www.scopus.com/inward/record.url?scp=13344270305&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=13344270305&partnerID=8YFLogxK

M3 - Conference contribution

SP - 708

EP - 713

BT - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

ER -