Global Security Using Human Face Understanding under Vision Ubiquitous Architecture System
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
Global Security Using Human Face Understanding under Vision Ubiquitous Architecture System

Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1056988

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1266

References:


[1] S.Shan, W.Gao, B.Cao and D.Zhao, "illumination normalization for robust face recognition with varying lighting conditions," Proc. IEEE International Workshop on AMFG, pp. 157-164, 2003.
[2] Jae-Ho Lee, "Automatic Video Management System Using Face Recognition and MPEG-7 Visual descriptors,"ETRI Journal, vol. 27, no. 6, pp.806-809, Dec. 2005.
[3] P.N. Belhumeour, J.P. Hespanha and D.J. Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19. no. 7, pp.711-720, 1997.