DocumentCode :
2641798
Title :
Real-time multiple face detection of pedestrian using hybrid GA
Author :
Suzuki, Hidekazu ; Minami, Mamoru
Author_Institution :
Dept. of Mech. Eng., Fukui Nat. Coll. of Technol., Japan
fYear :
2004
fDate :
3-6 Oct. 2004
Firstpage :
708
Lastpage :
713
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.
Keywords :
automated highways; face recognition; genetic algorithms; image colour analysis; object detection; real-time systems; search problems; security; tracking; human face recognition; human face tracking; human visual function; hybrid GA; hybrid genetic algorithm; image colour analysis; image processing; intelligent transportation systems; multiple target detection; pedestrian face detection; random search; real time multiple face detection; security systems; Cameras; Face detection; Face recognition; Humans; Image processing; Image recognition; Intelligent transportation systems; Object detection; Real time systems; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2004. Proceedings. The 7th International IEEE Conference on
Print_ISBN :
0-7803-8500-4
Type :
conf
DOI :
10.1109/ITSC.2004.1398988
Filename :
1398988
Link To Document :
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