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Erschienen in: Annals of Data Science 3/2015

01.09.2015

Modular Real-Time Face Detection System

verfasst von: Kaiyu Wang, Zhiming Song, Menglin Sheng, Ping He, Zhenan Tang

Erschienen in: Annals of Data Science | Ausgabe 3/2015

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Abstract

In this paper, a novel system architecture of face detection in possession of modular characteristic is proposed, and the corresponding face detection method is described, to match with the proposed architecture. First of all, the proposed architecture of face detection consists of two modules, namely, the coprocessor module of face detection based on FPGA and target system module, which hopes to implement finial face detection, based on general purpose CPU, and USB bus is used as the communication bridge between the two modules. Secondly, taking the characteristics of FPGA and general purpose CPU into consideration, face detection algorithm can be divided into two layers. The first layer of face detection algorithm based on skin color and eyes’ graylevel variation is implemented in the FPGA, and then the corresponding detection results and image are transmitted to the second module by USB bus so as to further detect face using the algorithm combining principle component analysis with support vector machine, which is referred to as the second layer of algorithm. Because the second layer of the algorithms are operations of float-point and loop, it implemented in the general purpose CPU. This architecture enables face detection to be implemented not only in high performance computing platform in possession of USB bus interface, but also in small terminal products and low-end embedded systems, where the performance of processor and the resource of hardware are limited. Actual testing results show that the proposed system architecture can implement real-time face detection for the images with 640 \(\times \) 480 resolution, and the detection accuracy is about 89 %.

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Literatur
1.
Zurück zum Zitat Wechsler H, Phillips JP, Bruce V, Soulie FF, Huang TS (eds) (1998) Face recognition: from theory to applications[M]. Springer, New York Wechsler H, Phillips JP, Bruce V, Soulie FF, Huang TS (eds) (1998) Face recognition: from theory to applications[M]. Springer, New York
2.
Zurück zum Zitat Buenaposada JM, Muñoz E, Baumela L (2008) Recognising facial expressions in video sequences. Pattern Anal Appl 11(1):101–116CrossRef Buenaposada JM, Muñoz E, Baumela L (2008) Recognising facial expressions in video sequences. Pattern Anal Appl 11(1):101–116CrossRef
3.
Zurück zum Zitat Nguyen D, Halupka D, Aarabi P et al (2006) Real-time face detection and lip feature extraction using field-programmable gate arrays. Syst Man Cybern Part B 36(4):902–912CrossRef Nguyen D, Halupka D, Aarabi P et al (2006) Real-time face detection and lip feature extraction using field-programmable gate arrays. Syst Man Cybern Part B 36(4):902–912CrossRef
4.
Zurück zum Zitat Kim TK, Lee SU, Lee JH, et al. (2002) Integrated approach of multiple face detection for video surveillance[C]//pattern recognition, 2002. Proceedings of 16th international conference on IEEE, 2: 394–397 Kim TK, Lee SU, Lee JH, et al. (2002) Integrated approach of multiple face detection for video surveillance[C]//pattern recognition, 2002. Proceedings of 16th international conference on IEEE, 2: 394–397
5.
Zurück zum Zitat Hjelmås E, Low BK (2001) Face detection: a survey. Comput Vis Image Underst 83(3):236–274CrossRef Hjelmås E, Low BK (2001) Face detection: a survey. Comput Vis Image Underst 83(3):236–274CrossRef
6.
Zurück zum Zitat Yang MH, Kriegman D, Ahuja N (2002) Detecting faces in images: a survey. Pattern Anal Mach Intell IEEE Trans 24(1):34–58CrossRef Yang MH, Kriegman D, Ahuja N (2002) Detecting faces in images: a survey. Pattern Anal Mach Intell IEEE Trans 24(1):34–58CrossRef
7.
Zurück zum Zitat Theocharides T (2006) Embedded hardware face detection[D]. The Pennsylvania State University Theocharides T (2006) Embedded hardware face detection[D]. The Pennsylvania State University
8.
Zurück zum Zitat McCready R (2000) Real-time face detection on a configurable hardware system. Springer, BerlinCrossRef McCready R (2000) Real-time face detection on a configurable hardware system. Springer, BerlinCrossRef
9.
Zurück zum Zitat Bigdeli A, Sim C, Biglari-Abhari M et al (2007) Face detection on embedded systems[M]// Embedded Software and Systems. Springer, Berlin pp 295–308 Bigdeli A, Sim C, Biglari-Abhari M et al (2007) Face detection on embedded systems[M]// Embedded Software and Systems. Springer, Berlin pp 295–308
10.
Zurück zum Zitat Acasandrei L, Barriga A (2012) FPGA implementation of an embedded face detection system based on LEON3[J] Acasandrei L, Barriga A (2012) FPGA implementation of an embedded face detection system based on LEON3[J]
11.
Zurück zum Zitat Yim M, Shen WM, Salemi B et al (2007) Modular self-reconfigurable robot systems [grand challenges of robotics]. Robot Autom Mag IEEE 14(1):43–52CrossRef Yim M, Shen WM, Salemi B et al (2007) Modular self-reconfigurable robot systems [grand challenges of robotics]. Robot Autom Mag IEEE 14(1):43–52CrossRef
12.
Zurück zum Zitat Underwood KD, Hemmert KS (2004) Closing the gap: CPU and FPGA trends in sustainable floating-point BLAS performance[C]//Field-Programmable Custom Computing Machines, 2004. FCCM 2004. 12th Annual IEEE Symposium on IEEE, 219–228 Underwood KD, Hemmert KS (2004) Closing the gap: CPU and FPGA trends in sustainable floating-point BLAS performance[C]//Field-Programmable Custom Computing Machines, 2004. FCCM 2004. 12th Annual IEEE Symposium on IEEE, 219–228
13.
Zurück zum Zitat Rowley HA, Baluja S, Kanade T (1998) Neural network-based face detection. Pattern Anal Mach Intell IEEE Trans 20(1):23–38CrossRef Rowley HA, Baluja S, Kanade T (1998) Neural network-based face detection. Pattern Anal Mach Intell IEEE Trans 20(1):23–38CrossRef
14.
Zurück zum Zitat Bailey DG, Johnston CT (2007) Single pass connected components analysis[C]//Proceedings of image and vision computing New Zealand, pp 282–287 Bailey DG, Johnston CT (2007) Single pass connected components analysis[C]//Proceedings of image and vision computing New Zealand, pp 282–287
Metadaten
Titel
Modular Real-Time Face Detection System
verfasst von
Kaiyu Wang
Zhiming Song
Menglin Sheng
Ping He
Zhenan Tang
Publikationsdatum
01.09.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Annals of Data Science / Ausgabe 3/2015
Print ISSN: 2198-5804
Elektronische ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-015-0064-6

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