Face Recognition in Mobile Wireless Sensor Networks

A new wireless sensing network paradigm is presented for face recognition applications. In addition to the flexibility the face recognition system gains by integrating into a wireless sensor network, we take it further by introducing mobility into the network to improve the sensing coverage area and cost efficiency. To implement these goals, a multilayered network structure and Gauss-Markov mobility model are proposed. Furthermore, analysis of the sensing coverage area is given. Besides, some of the potential application scenarios based on the proposed paradigm are also presented. According to the simulation, the whole system achieves high recognition rate and energy efficiency compared to stationary network.

[1]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[2]  Viswanath Tolety,et al.  Load Reduction in Ad Hoc Networks Using Mobile Servers , 1999 .

[3]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[4]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Rekha Jain,et al.  Wireless Sensor Network -A Survey , 2013 .

[6]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[7]  Lisa Ann Osadciw,et al.  Increased Efficiency of Face Recognition System using Wireless Sensor Network , 2013 .

[8]  Waylon Brunette,et al.  Data MULEs: modeling a three-tier architecture for sparse sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[9]  Chris Freiling,et al.  Axioms of symmetry: Throwing darts at the real number line , 1986, Journal of Symbolic Logic.

[10]  B. Ripley,et al.  Introduction to the Theory of Coverage Processes. , 1989 .

[11]  Zygmunt J. Haas,et al.  A new routing protocol for the reconfigurable wireless networks , 1997, Proceedings of ICUPC 97 - 6th International Conference on Universal Personal Communications.

[12]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[13]  Sajal K. Das,et al.  Data Collection in Wireless Sensor Networks with Mobile Elements: A Survey , 2011, TOSN.

[14]  Yongsheng Gao,et al.  Face recognition across pose: A review , 2009, Pattern Recognit..

[15]  J. Seaman.  Introduction to the theory of coverage processes , 1990 .

[16]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[17]  Kevin R. Fall,et al.  A delay-tolerant network architecture for challenged internets , 2003, SIGCOMM '03.

[18]  Roberto Brunelli,et al.  Face Recognition: Features Versus Templates , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Rae-Hong Park,et al.  Recognition of human front faces using knowledge-based feature extraction and neurofuzzy algorithm , 1996, Pattern Recognit..

[20]  Farzin Mokhtarian,et al.  Efficient face recognition for wireless surveillance systems , 2007 .

[21]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..

[22]  Amotz Bar-Noy,et al.  Mobile users: To update or not to update? , 1994, Proceedings of INFOCOM '94 Conference on Computer Communications.

[23]  Hamid Aghajan,et al.  Collaborative Face Orientation Detection in Wireless Image Sensor Networks , 2006 .

[24]  Mostafa H. Ammar,et al.  Message ferrying: proactive routing in highly-partitioned wireless ad hoc networks , 2003, The Ninth IEEE Workshop on Future Trends of Distributed Computing Systems, 2003. FTDCS 2003. Proceedings..