Review on- GAIT RECOGNITION WITH K-REANS USING SVM, MDA and LDA

Volume: 3    Issue: 3

Year of Publication: 2016

Pages: (30-34)

Authors: Anjana, Mandeep

Download Full Text (PDF)

Abstract

Human recognition methods are used for identifying individuals on the basis of different biometrics as iris, face, fingerprint, retina, voice patterns and signatures. Among these generally all the biometric traits require a user’s cooperation, either via physical contact or close proximity. Such schemes are unable to identify a person at some distance. To overcome this, gait recognition is introduced in biometrics. It is relatively new technique of recognition without these disadvantages. Gait biometric recognize an individual on the basis of their walking pattern. It is a biometric that comes under the type of behavioral characteristics. This paper aims to confer number of techniques such as SVM, K-Means, LDA and MDA that can be application for human identification on the basis of gait biometrics.

References

1. Niyogi, S., Adelson, E:, “Analyzing and recognizing walking figures in XYT,”. In IEEE Computer society conference on computer vision and pattern recognition, Seattle, Wash, USA, pp. 469-474(1994).

2. C.Y.Yam, M.S Nixon and J.N, “Extendedmodel based automatic gait recognition of walkingand running”, 3rdproc. AVBPA 2001, pp 278-283.

3. M. Jeevan, Neha Jain, M. Hanmandlu and Girija Chetty. “Gait Recognition Based on Gait Pal and Pal Entropy Image”. IEEE International Conference, 2013.

4. Maodi Hu, Yunhong Wang, Zhaoxiang Zhang and De Zhang. “Gait-Based Gender Classification Using Mixed Conditional Random Field” IEEE Transactions on Systems, Mans and Cybernetics, Part B: Cybernetics, 2011.

5. S. Yu, T. Tan, K. Huang, K. Jia, and X. Wu. “A study on gait-based gender classification”. IEEE Transactions on Image Processing, 18(8):1905-1910, 2009.

6. X. Li, S. Maybank, S. Yan, D. Tao, and D. Xu. “Gait components and their application to gender recognition”.IEEE Transactions on Systems, Mans, and Cybernetics, Part C: Applications and Reviews, 38(2):145-155, 2008.

7. X. Huang and N. V. Boulgouris. “Gait recognition with shifted energy image and structural features extraction”. IEEE Transactions on Image Processing, 21(4):2256-2268, 2012.

8. Ahmad Puad Ismail, Murad Alaqtash, A. Bashir Khalid, “Model-based human walk information for sex recognition”, vol. 26, pp. 123-129, 2007

9. Qiong Cheng, Bo Fu and Hui Chen, “Gait Recognition Based on PCA and LDA”.International Computer Science and Computational Technology, pp. 124-127, Dec. 2009.

10. C. Y. Yam, M. S. Nixon, and J. N. Carter. “Gait recognition by walking and running: A model-based approach”.In Proceeding of 5th Asian Conference on Computer Vision, 2002.

11. Ai-Hua, Wang Ji, Wei Liu, “Gait Recognition Method Based on Positioning human body joints” International Conference on wavelet analysis and pattern recognition, 2-4 Nov 2007.

12. J.Han and B.Bhanu, “Individual recognition using gait energy image,” IEEE Trans.on pattern analysis and machine intelligence, vol. 28, no.2,pp. 316-322, Feb.2006.

13. Anupam shukla, Ritu Tiwari, Sanjeev Sharma, “Identification of people using gait biometrics”, International journal of machine learning and computing, Vol.1, No. 4, October 2011.

14. Yi-Bo Li, Tian-Xiao jiang, Zhi-Hua Qiao, Hong-juan Qian, “General method and development actuality of gait recognition”, International conference on wavelet analysis and pattern recognition, Beijing, china, 2-4 Nov.2007.

15. Lili Liu, Wei Qin, Yilong Yin, Ying Li, “Gait recognition based on outermost contour,” International Journal of computational intelligence systems, Vol.4, No.5, September, 2011.

16. S.J.McKenna, S.Jabri, Z.Duric, “Tracking group of people,” Comput. Vis. Image Understanding, vol.80, no. 1,pp. 42-56.

17. Su-Li XY, Qian-jin ZHANG, “gait recognition using fuzzy principal component analysis”, 2nd International Confrence on e-business and information system security, IEEE, 27 may 2010.

Keywords

GAIT, Biometric, Support Vector Machine (SVM), LDA, K-Means, recognition, MDA.