Gait Feature Based on Human Identification & Classification by Using Artificial Neural Network and Project Management Approaches for Its Implementation

  • Authors

    • Waqar Tariq
    • Muhammad Lutfi Othman
    • Shameem Akhtar
    • Fareeha Tariq
    2019-01-18
    https://doi.org/10.14419/ijet.v8i1.7.25968
  • Gait, Biometrics, Human Identification, Artificial Neural Network, Project management, PMP, PMIS, AC, BAC

  • With the increased threat of terrorism and identity theft, human recognition is one of the basic elements of present era’s security applications installed in commercial malls, banks, hospitals, military installations, airports, religious places etc. The basic aim of this research study is to design and implement an ANN based human recognition and monitoring system.  This system uses Gait property of people to classify them through their age, gender, and group. Furthermore, the implementation and testing phase is conducted according to the principle and approaches of Project Management in order to tackle the constraint of both time and cost, also to make it a well implemented ICT project which can also follow the same approach as used commercially .Taking a tracking approach of the cost, time and quality made it easy to judge that this project is commercially viable.

     

     

  • References

    1. [1] Fingerprint Recognition, Paper by WUZHILI (Department of Computer Science & Engineering, Hong Kong Baptist University) 2002

      [2] Mashaghi A, Katan A (2013). "A physicist's view of DNA". De Physicus 24e (3): 59–61.

      [3] R Wildes. Iris recognition: an emerging biometric technology. Proceedings IEEE, Vol. 85, No. 9, 1997.

      [4] Y. Zhu, T. Tan, Y. Wang. Biometric personal identification based on iris patterns. Proceedings of the 15th International Conference on Pattern Recognition, Spain, Vol. 2, 2000

      [5] Face Recognition Data, University of Essex, UK, Face 94, http://cswww.essex.ac.uk/mv/all faces/faces94.html

      [6] Adler, A., Youmaran, R. And Loyka, S. (2006) Towards a Measure of Biometric Information retrieved August 2, 2006 fromhttp://www.sce.carleton.ca/faculty/adler/publications/2006/youmaran-ccece2006-biometric-entropy.pdf.

      [7] H. Ali, Jamal Dargham, Chekima Ali, Ervin Gobin Moung; “Gait Recognition using Principal Component Analysisâ€, 3rd International Conference on Machine Vision (ICMV), China, Hong Kong, December 28-30, 2010, pp: 539-543.

      [8] Feng Liu, L., Jia W., and Hai Z. Y.; 2009. “Survey of Gait Recognitionâ€. Springer-Verlag Berlin Heidelberg, ICIC 2009, LNAI 5755, pp: 652-659.

      [9] Sudeep Sarkar, P. Jonathon Phillips, Zongyi Liu, Isidro Robledo Vega, PatrickGrother, and Kevin W. Bowyer. The humanID gait challenge problem: Data sets,performance, and analysis. IEEE Transactions on Pattern Analysis and MachineIntelligence, 27(2):162–177, 2005

      [10] Peter K. Larsen, Erik B. Simonsen, and Niels Lynner up. Gait analysis in forensicmedicine. In SPIE Electronic Imaging (Videometrics IX), 2007.

      [11] Center for Biometrics and Security Research, CASIA. http://www.cbsr.ia.ac.cn.

      [12] j. Han and B. Bhanu, “Performance Prediction for Individual Recognition By Gait,†Pattern Recognition Letters, vol. 26, no. 5, pp. 615-624, Apr. 2005

      [13] X. Huang and N.V. Boulgouris, “Gait Recognition using Multiple Viewsâ€. Proceeding of the IEEE International Conference on Acoustics, Speech, and Signal Processing, 2008, pp: 1705-1708.

      [14] Y. Guo, G. Tian, "Gait Recognition Based on Anatomical Knowledge†Intelligent Control and Automation, WCICA 7th World Congress, 2008, pp: 6803 – 6806.

      [15] Waqar Tariq a, Lutfi Othman b, Norman b. Mariun c, Noor Izzri b. Abd. Wahab d, “What Smart Building Management System can offer: Brief Discussion by taking Malaysian power infrastructure as a sample Advancesâ€. in Electrical and Electronic Engineering (ISSN 1804-3119) International Journal of Computer and Electrical, Engineering (IJCEE).

      [16] D. Sharmila and E. Kirubakaran; “Image and Formula Based Gait Recognition Methodsâ€. International Journal of Computer and Electrical Engineering, Vol. 2, No. 2, April 2010, pp: 381-388.

      [17] Waqar Tariq, Mohammad Lutfi Othman, Noor Izzri Abdul Wahab, Mansoor Ebrahim, A Review on ESCO’s Challenges and Project Management as a Solving Tool Indonesian Journal of Electrical Engineering and Computer Science Vol. 12, No. 1, October 2018, pp. 269~274 ISSN: 2502-4752, DOI: 10.11591/ijeecs. v12.i1.pp269-274

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  • How to Cite

    Tariq, W., Lutfi Othman, M., Akhtar, S., & Tariq, F. (2019). Gait Feature Based on Human Identification & Classification by Using Artificial Neural Network and Project Management Approaches for Its Implementation. International Journal of Engineering & Technology, 8(1.7), 133-137. https://doi.org/10.14419/ijet.v8i1.7.25968