Browse > Article

Development of Rotation Invariant Real-Time Multiple Face-Detection Engine  

Han, Dong-Il (Dept. of Computer Engineering, Sejong University)
Choi, Jong-Ho (Dept. of Computer Engineering, Sejong University)
Yoo, Seong-Joon (Dept. of Computer Engineering, Sejong University)
Oh, Se-Chang (Dept. of Information & Communication, Sejong Cyber University)
Cho, Jae-Il (Robot Research Department, ETRI)
Publication Information
Abstract
In this paper, we propose the structure of a high-performance face-detection engine that responds well to facial rotating changes using rotation transformation which minimize the required memory usage compared to the previous face-detection engine. The validity of the proposed structure has been verified through the implementation of FPGA. For high performance face detection, the MCT (Modified Census Transform) method, which is robust against lighting change, was used. The Adaboost learning algorithm was used for creating optimized learning data. And the rotation transformation method was added to maintain effectiveness against face rotating changes. The proposed hardware structure was composed of Color Space Converter, Noise Filter, Memory Controller Interface, Image Rotator, Image Scaler, MCT(Modified Census Transform), Candidate Detector / Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor / Color Overlay Processor. The face detection engine was tested using a Virtex5 LX330 FPGA board, a QVGA grade CMOS camera, and an LCD Display. It was verified that the engine demonstrated excellent performance in diverse real life environments and in a face detection standard database. As a result, a high performance real time face detection engine that can conduct real time processing at speeds of at least 60 frames per second, which is effective against lighting changes and face rotating changes and can detect 32 faces in diverse sizes simultaneously, was developed.
Keywords
Face-detection; MCT; Adaboost; Rotation Transformation; Hardware Implementation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 이수현, 정용진, "얼굴 검출을 위한 SoC 하드웨어구현 및 검증", 전자공학회 논문지 제44권 SD 편, 제 4호, 대한전자공학회, 2007년 4월.
2 Najwa Aaraj, Srivaths Ravi, Anand Raghunathan and Niraj K. Jha, "Hybrid architectures for efficient and secure face authentication in embedded systems", IEEE Transaction on VLSI Systems, Vol.15, no. 3, pp.296-308, March 2007.   DOI
3 한동일, 조현종, 최종호, 조재일, "고성능 실시간 얼굴 검출 엔진의 설계 및 구현", 전자공학회 논문지, 제47권 SP 편, 제 3호, 대한전자공학회, 2010년 3월
4 Georghiades, A. : Yale Face Database, Center for computational Vision and Control at Yale University, http:// cvc.yale.edu/ projects/yalefaces/ yalefaces.html
5 CMU/VASC Image Database, http: // asc.ri.cmu. edu /idb /html/ face/index.html
6 The BioID face database:[http://www.bioid. com/ downloads /facedb /facedatabase. html]
7 R. McCready, "Real-time face detection on a configurable hardware platform, " M.S. thesis, Dept. Elect. Comput. Eng., Univ. Toronto, Toronto, On, Canada, 2000.
8 Duy Nguyen, David Halupka, Parham Aarabi, and Ali Sheikholeslami, "Real time Face detection and Lip feature extraction using Field-Programmable Gate Arrays", IEEE Transactions on SYSTEMS, MAN AND CYBERNETICS-ART B: CYBERNETICS, Vol. 36, no. 4, pp.902-912, AUGUST 2006.   DOI
9 Q. Wang, W. Yang, H. Wang, J. Yang and Y. Jheng, "Face Detection Using Binary Template Matching and SVM", Pacific Rim International Conference on Artificial Intelligence (PRICAI), pp. 1237-1241, China, Aug. 2006.
10 Yea-Shuan Huang and Wei-Cheng Lie, "Face Detector with Oriented Multiple Templates", International MultiConference of Engineers and Computer Scientists, Hong Kong, March, 2008.
11 Ermioni Marami and Anastasios Tefas, "Face Detection Using Particle Swarm Optimizations and Support Vector Machines", Hellenic Conference on Artificial Intelligence (SETN), pp. 369-374, Greece, May. 2010.
12 Yoav Freund and Robert E. Schapire. "A decision-theoretic generalization of on-line learning and an application to boosting" in Journal of Computer and System Sciences, pp. 119-139, 1997.
13 Samir Nanavat, Michael Thieme and Raj Nanavati. "Biometrics", Wiley, pp.63-75, 2002.
14 Bongjin Jun, Daijin Kim, "Robust real-time face detection using face certainty map", Lecture Notes in Computer Science, Springer Berlin / Heidelberg, pp. 29-38, 2009.
15 P. Viola and M. Jones, "Fast and robust classification using asymmetric AdaBoost and a detector cascade", in NIPS 14, 2002, pp. 1311-1318.
16 Jianxin Wu, S. Charles Brubaker, Matthew D. Mullin, and James M. Rehg, Member, "Face Asymmetric Learning for Cascade Face Detection", IEEE Transaction on Pattern Analysis and Machine Intelligence,p. 1-13, 2008.
17 Junguk Cho, Shahnam Mirzaei, Jason Oberg, Ryan Kastner, "Fpga-based face detection system using Haar classifiers", Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays, Portal.acm.org, p. 103-112, 2009.
18 Ming-Hsuan Yang, Dan Roth and Narendra Ahuja. "A snow-based face detector". In Advances in Neural Information Processing Systems 12 (NIPS 12), pp.855-861. MIT Press, 2000.
19 Sung, K.K., Poggio, T, "Example-based learning for view-based human face detection", IEEE Transactions on Pattern Analysis and Machine Intelligence 20, p. 39-51, 1998.   DOI   ScienceOn
20 S. Romdhani, P. Torr, B. Schoelkopf, and A. Blake, "Computationally efficient face detection", in Proc. ICCV, 2001, pp. 695-700.
21 Chang Huang, Haizhou Ai, Yuan Li, and Shihong Lao, "High-Performance Rotation Invariant Multiview Face Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, No. 4, pp. 671-686, April, 2007.   DOI
22 Paul Viola and Michael J. Jones, "Robust real-time face detection" In International Journal of Computer Vision, pp. 137-154, 2004.
23 Bernhard Fröba and Andreas Ernst, "Face detection with the Modified Census Transform", IEEE International Conf. On Automatic Face and Gesture Recognition(AFGR), pp. 91-96, Seoul, Korea, May. 2004.