Square patch feature based face detection architecture for high resolution smart camera

Recognizing faces in a crowd in real-time is a key feature which would significantly enhance Intelligent Surveillance Systems. Previously we proposed a high resolution smart camera system that can be used for crowd surveillance. The challenge is with the increasing speed and resolution of the im...

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Main Authors: Mohd Mustafah, Yasir, Bigdeli, Abbas, Azman, Amelia Wong, Lovell, Brian
格式: Conference or Workshop Item
语言:English
出版: ACM 2010
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在线阅读:http://irep.iium.edu.my/28298/
http://irep.iium.edu.my/28298/
http://irep.iium.edu.my/28298/1/Square_Patch_Feature_Based_Face_Detection_Architecture_for_High_Resolution_Smart_Camera.pdf
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总结:Recognizing faces in a crowd in real-time is a key feature which would significantly enhance Intelligent Surveillance Systems. Previously we proposed a high resolution smart camera system that can be used for crowd surveillance. The challenge is with the increasing speed and resolution of the image sensors, a fast and robust face detection system is required for real time operation. In this paper, we proposed a face detection architecture that is suitable to be implemented on a smart camera system. The face detection algorithm is based on a new weak classifier type that we called square patch feature. The targeted platform is a low cost Spartan-3 FPGA. From The simulation result shows that the proposed face detection architecture could speed up the equivalent software based face detector up to 12 times. Parallelizing the feature classification modules could improve the performance further.