Multi-Faces Image Recognition
Affiliation(s)
Division of Communication & Information, Baekseok University, Cheonan, Korea. National Information Society Agency, Seoul, Korea. Department of Biomedical Engineering, Konyang University, Nonsan, Korea.
Division of Communication & Information, Baekseok University, Cheonan, Korea. National Information Society Agency, Seoul, Korea. Department of Biomedical Engineering, Konyang University, Nonsan, Korea.
ABSTRACT
The paper suggests a great improvement in the recognition rate and speed by overcoming the disadvantage of 3D image processing taking a long time as well as that of 2D images weak in postures through correcting shooting angles with 3D data taken by multi cameras followed by application of the developed hybrid face recognition technology.
The paper suggests a great improvement in the recognition rate and speed by overcoming the disadvantage of 3D image processing taking a long time as well as that of 2D images weak in postures through correcting shooting angles with 3D data taken by multi cameras followed by application of the developed hybrid face recognition technology.
Cite this paper
J. Han, J. Lee and G. Kim, "Multi-Faces Image Recognition," Open Journal of Applied Sciences, Vol. 3 No. 1, 2013, pp. 53-57. doi: 10.4236/ojapps.2013.31B011.
J. Han, J. Lee and G. Kim, "Multi-Faces Image Recognition," Open Journal of Applied Sciences, Vol. 3 No. 1, 2013, pp. 53-57. doi: 10.4236/ojapps.2013.31B011.
References
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[1] Frederic Dufaux, “Scrambling for Privacy Protection in Video Surveillance Systems”, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECH-NOLOGY, 2008, 18(8). [2] Kenichi YABUTA, “Privacy Protection by Masking Moving Objects for Security Cameras”, IIEICE Transactions on Funda-mentals of Electronics, Communications and Computer Sciences, Volume E92.A, Issue 3, 2009 : 919-927. [3] Mitsuji Muneyasu, “An Implementation of Privacy Protection for a Surveillance Camera Using ROI Coding of JPEG2000 with Face Detection”, IIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2009, E92-A(11) : 2858-2861. [4] E. Yu and J. Aggarwal, "Human action recognition with extremities as semantic posture representation," Proc. Int. Conf. Computer Vision, Pattern Recognition, 2009: 1-8. [5] TI, “TMS320C64x+ DSP Image/Video Processing Library Programmer's Guide,” Texas Instruments, Dallas, Texas, May, 2008. [6] TI, “Vision Library Application Programming Interface Reference Guide,” Texas Instruments, Dallas, Texas, Nov., 2009. [7] Chris Stauffer and W.E.L Grimson, “Adaptive Background Mixture Models for Real-time Tracking,” Proc.IEEE Conference on Computer Vision & Pattern Recognition, 1999, 2 : 246- 252. [8] A Al-Habaibeh, F Shi, N Brown, D Kerr, M Jackson and R M Parkin, "A novel approach for quality control system using sensor fusion of infrared and visual image processing for laser sealing of food containers," MEASUREMENT SCIENCE AND TECHNOLOGY, 2004 : 1995~2000. [9] Philippe Simard, Norah K. Link, Ronald V. Kruk, "Evaluation of Algorithms for Fusing Infrared and Synthetic Imagery," Enhanced and synthetic vision 2000. Conference, Orlando FL, 2000, 4023 : 127-138. [10] C. Wren, A. Azerbayejani, T. Darrel, and A. Pentland, “Pfinder: real-time tracking of the human body.” IEEE Trans. Pattern Analysis and Machine Intelligence, 1997, 19(7): 780-785. [11] S. Kang, J. Paik, A. Koschan, B. Abidi, and A. Abidi, “Real-time video tracking using PTZ cameras.” Proc. SPIE 6th International Conference on Quality Control by Artificial Vision, 2003, 5132 : 103-111. [12] P. Azzari, L. Stefano, and A. Bevilacqua, “An effective real-time mosaicing algorithm apt to detect motion through background subtraction using a PTZ camera.” IEEE Conf. Advanced Video and Signal-Based Surveillance, 2005 : 511-516. [13] G. A. Ramirez and O. Fuentes, “Multi-pose face detection with asymmetric HAAR features.” Applications of Computer Vision, 2008. WACV 2008. IEEE Workshop, 2008 : 1-6