i-manager Publications

Gait Based Human Age Classification using Random Forest Classifier

M. Hema*, K. Babulu**, N. Balaji***

*-*** Department of Electronics and Communication Engineering, UCEV, JNTUK University College of Engineering, Vizianagaram, Andhra Pradesh, India.

Periodicity:June - August'2019
DOI : https://doi.org/10.26634/jpr.6.2.16607

Abstract

In recent times, classification of human age has gained more attention. In this paper we propose to use gait identification points mainly to classify human's age based on their way of walking style. In this paper, we propose a Gait energy image Projection Model (GPM) for gait representation, which represents both Gait energy image Longitudinal Projection (GLP) and Gait energy image Transverse Projection (GTP) during a gait cycle. The proposed method mainly focuses on four parameters, namely head movement, body size, arm movement, and stride length. Regarding classification of age, OU-ISIR dataset is considered and the random forest is selected as the classifier. Moreover, the obtained experimental results are compared with the existing ones like FED, GEI, and SM. Further, descriptors are fused to check whether they get better results or not.

Keywords

Gait Energy Image Projection Model (GPM), GLP, GTP, Age Classification.

How to Cite this Article?

Hema , M., Babulu, K., & Balaji, N. (2019). Gait Based Human Age Classification using Random Forest Classifier. i-manager’s Journal on Pattern Recognition, 6(2), 1-7. https://doi.org/10.26634/jpr.6.2.16607

References

[1]. Cuntoor, N., Kale, A., & Chellappa, R. (2003, April). Combining multiple evidences for gait recognition. In 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings (ICASSP'03). (Vol. 3, pp. 3-33). IEEE. https://doi.org/10.1 109/ICASSP.2003.1199100

[2]. Dupuis, Y., Savatier, X., & Vasseur, P. (2013). Feature subset selection applied to model-free gait recognition. Image and Vision Computing, 31(8), 580-591. https://doi.org/10.1016/j.imavis.2013.04.001

[3]. Han, H., & Jain, A. K. (2014). Age, gender and race estimation from unconstrained face images. Department of Computer Science Engineering, Michigan State Univ., East Lansing, MI, USA, MSU Tech. Rep (MSU-CSE- 14-5), 87.

[4]. Han, H., Otto, C., & Jain, A. K. (2013, June). Age estimation from face images: Human vs. machine performance. In 2013 International Conference on Biometrics (ICB) (pp. 1-8). IEEE. https://doi.org/10.11 09/ICB.2013.6613022

[5]. Han, J., & Bhanu, B. (2005). Individual recognition using gait energy image. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(2), 316-322. https://doi.org/10.1109/TPAMI.2006.38

[6]. Hayashi, J. I., Yasumoto, M., Ito, H., & Koshimizu, H. (2002, August). Age and gender estimation based on wrinkle texture and color of facial images. In Object Recognition Supported by User Interaction for Service Robots (Vol. 1, pp. 405-408). IEEE. https://doi.org/10.1109/ ICPR.2002.1044736

[7]. Hema, M., Babulu, K., & Balaji, N. (2019). Gait recognition and classification using random forest algorithm. Journal of Advance Research in Dynamical & Control system, 11(2), 281-289.

[8]. Huang, G., & Wang, Y. (2007, November). Gender classification based on fusion of multi-view gait sequences. In Asian Conference on Computer Vision (pp. 462-471). Springer: Berlin, Heidelberg.

[9]. Huang, P. S. (2001). Automatic gait recognition via statistical approaches for extended template features. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 31(5), 818-824 https://doi.org/10. 1109/3477.956044

[10]. Iwama, H., Okumura, M., Makihara, Y., & Yagi, Y. (2012). The OU-ISIR gait database comprising the large population dataset and performance evaluation of gait recognition. IEEE Transactions on Information Forensics and Security, 7(5), 1511-1521. https://doi.org/10.1109/ TIFS.2012.2204253

[11]. Jean, F., Bergevin, R., & Albu, A. B. (2005, May). Body tracking in human walk from monocular video sequences. In the 2^nd Canadian Conference on Computer and Robot Vision (CRV'05) (pp. 144-151). IEEE. https://doi.org/10.1109/CRV.2005.24

[12]. Khryashchev, V., Priorov, A., & Ganin, A. (2014, October). Gender and age recognition for video analytics solution. In 2014 IEEE Applied Imagery Pattern Recognition Workshop (AIPR) (pp. 1-6). IEEE. https://doi.org/10.1109/AIPR.2014.7041914

[13]. Liu, Y., Collins, R., & Tsin, Y. (2002, May). Gait sequence analysis using frieze patterns. In European Conference on Computer Vision (pp. 657-671). Berlin, Heidelberg: Springer. https://doi.org/10.1007/3-540- 47967-8_44

[14]. Lu, J., & Tan, Y. P. (2010). Gait-based human age estimation. IEEE Transactions on Information Forensics and Security, 5(4), 761-770. https://doi.org/10.1109/ TIFS.2010.2069560

[15]. Makihara, Y., Okumura, M., Iwama, H., & Yagi, Y. (2011, October). Gait-based age estimation using a whole-generation gait database. In 2011 International Joint Conference on Biometrics (IJCB) (pp. 1-6). IEEE. https://doi.org/10.1109/IJCB.2011.6117531

[16]. Tafazzoli, F., & Safabakhsh, R. (2010). Model-based human gait recognition using leg and arm movements. Engineering Applications of Artificial Intelligence, 23(8), 1237-1246. https://doi.org/10.1016/j.engappai.2010. 07.004

[17]. Wang, L., Ning, H., Tan, T., & Hu, W. (2004). Fusion of static and dynamic body biometrics for gait recognition. IEEE Transactions on Circuits and Systems for Video Technology, 14(2), 149-158. https://doi.org/10.1109/ TCSVT.2003.821972

[18]. Zhang, R., Vogler, C., & Metaxas, D. (2004, June). Human gait recognition. In 2004 Conference on Computer Vision and Pattern Recognition Workshop (pp.18-18). IEEE. https://doi.org/10.1109/CVPR.2004.361

[19]. Zhuang, X., Zhou, X., Hasegawa-Johnson, M., & Huang, T. (2008, December). Face age estimation using patch-based hidden markov model supervectors. In 2008 19^th International Conference on Pattern Recognition (pp. 1-4). IEEE. https://doi.org/10.1109/ICPR. 2008.4761364

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.