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...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
ACM
2010
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| Subjects: | |
| Online Access: | 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 |
| Summary: | 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. |
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