Research on Face Recognition Technology of Real-Time Video High Performance Similarity

Abstract:

A new similarity measurement standard is proposed, namely background similarity matching. Learning algorithm based on kernel function is utilized in the method for feature extraction and classification of face image. Meanwhile, a real-time video face recognition method is proposed, image binary algorithm in similarity calculation is introduced, and a video face recognition system is designed and implemented [1-2]. The system is provided with a camera to obtain face images, and face recognition is realized through image preprocessing, face detection and positioning, feature extraction, feature learning and matching. Design, image preprocessing, feature positioning and extraction, face recognition and other major technologies of face recognition systems are introduced in details. Lookup mode from top down is improved, thereby improving lookup accuracy and speed [3-4]. The experimental results showed that the method has high recognition rate. Higher recognition rate still can be obtained even for limited change images of face images and face gesture with slightly uneven illumination. Meanwhile, training speed and recognition speed of the method are very fast, thereby fully meeting real-time requirements of face recognition system [5]. The system has certain face recognition function and can well recognize front faces.

• Periodical: Applied Mechanics and Materials (Volumes 713-715)
• Pages: 2160-2164
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.713-715.2160
• Online since: January 2015
• Authors: Zhao Nan Yang*, Shu Zhang
• Keywords: Binarization, Database, Face Recognition Technology, Similarity

References

[1] R . He , W . Zheng, B . Hu, IEEE Transactions on Neural Networks and Learning Systems, Vol. 24-28(2013), p.35−46.

[2] C. Wang, Y. Wang, Z . Zhang, Springer Press, Vol. 12-16(2012), p.1−8.

[3] B . Raducanu, F. Dornaika. Springer Press, Vol. 24-27(2012), p.566−575.

[4] R . Gottumukkal, V. Asari. Proceeding of ACM Great Lakes Symposium on VLSI, Vol. 14-17( 2003), pp.157-160.

[5] H . Neo, A. Jin, Washington: ACM Press, Vol. 14-18(2004), p.192−202.

[6] V . Nhat , S. Lee, Cairns: Springer Press, Vol. 2-6(2005), p.311−318.

[7] Pham P, Tuytelaars T, Moens M, IEEE Transactions on MultiMedia, Vol. 10-14( 2011), p.44−55.