The week's pick
Reseach Article
Gait Analysis for Human Identification by using BPNN with LDA and MDA Classifiers
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 127 - Number 11 |
| Year of Publication: 2015 |
| Authors: Ira Gaba, Satinder Pal Ahuja |
10.5120/ijca2015906547
|
Ira Gaba, Satinder Pal Ahuja . Gait Analysis for Human Identification by using BPNN with LDA and MDA Classifiers. International Journal of Computer Applications. 127, 11 ( October 2015), 51-56. DOI=10.5120/ijca2015906547
Abstract
In this paper BPNN performance for the gait analysis with using the different modulation techniques i.e LDA and MDA. Gait Analysis is the new technique in the biometric identification, the gait have more advantages over the field of biometric systems like face recognition, finger printing etc. Gait Analysis is a method by which individual can be recognized by the manner of walk. Less unobtrusive gait recognition system over the other biometric traits is the main advantage. i.e. it offers the identification of an individual at a particular distance, without any physical interference or contact with an individual and can be easily apply on the low resolution image frames as well. In this paper, firstly the video of an individual in captured, secondly background subtraction is applied on that so as to remove the unwanted information, thirdly feature extraction is carried out to extract the various parameters by using the Hanavan’s model, and finally the recognition is performed by using BPNN+LDA and BPNN+MDA techniques, are used for the training and the testing purposes, and the matching can also be performed on the basis of CBIR. All the processes are performed on the gait database and the input video.
References
- C. BenAbdelkader, R. Culler and L. Davis, “Stride and Cadence as a Biomertic in Automatic Person Identification and Verification” in Proceeding International Conference Automatic Face and Gesture Recognition, pp.372-377, 2002.
- Qinghan,“Technology review- Biometrics Technology, Application, Challenge and Computational Intelligence Solution”,IEEE Computational Intelligence Magazine, Vol 2,pp5-25,2007.
- Boulgouris, N.V Plataniotis, K.N Hatzinakos, “ An Angular Transform of Gait Sequences for Gait Assisted Recognition”, In: Proc.IEEE int. Conf. Image Processing Singapore, pp. 857-860, 2004.
- M. Pushparani, D. Sasikala, “A Survery of Gait Recognition approach using PCA and ICA”, Global Journal of Computer Science and Technology Network, Web & Security, Vol. 12, Issue 10, Version 1.0, May 2012.
- Lili Li, Yilong Yin, Wei Qin, Ying Li,“Gait Recognition Based on Outer Contour”,in International Journal Of Computational Intelligence Systems, Vol.4,No.5, pp. 1090-1099, March2012.
- A Hayder, J.Dargham, A. Chekima and G.M. Ervin, “Person Identification Using Gait”, in International Journal of Computer and Electrical Engineering, Vol. 3, No. 4, pp. 477-482, August 2011.
- Liang Wang, Tieniu Tan, Huazhong Ning and Weiming Hu, "Silhouette Analysis - Based Gait Recognition for Human Identification" IEEE transactions on Pattern Analysis and Machine Intelligence, Vol. 25, No. 12, December 2003.
- Jin Wang, Mary She, Saeid Nahavandi, Abbas Kouzani, “A Review of Vision-Based Gait-Recognition methods for Human Identification, in DICTA: Proceedings of the Digital Image Computing: Techniques and Application, IEEE, Piscataway,pp. 320-327, 2010.
- Stevan Rudinac, Goran Zajic, Marija Uscumlic and Maja Rudinac, “Comparison of CBIR Systems with Different Number of Feature Vector Components”, in IEEE Second International Workshop on Semantic Media Adaptation and Personalization, pp. 199-204, 2007.
- Jianlin Zhang and Wensheng Zou, “Content-based Image Retrieval Using Color and Edge Directions Features ”, in IEEE pp. 456-462, 2010.
- K. Velmurugan, Dr. S. Santhosh Baboo,“ Content- Based Image Retrieval using SURF and Color Moments ”,in Global Journal of Computer Science and Technology, Vol. 11, Issue 10, 2011.
- Ernest Istook, Tony Martinez, ,“ Improved Back-propagation Learning in Neural Networks with Windowed Momentum”, in International Journal of Neural Systems, Vol. 12, no. 3&4, pp. 303-318.
- A. A. Minai, and R.D. Williams, ,“ Acceleration of Back-propagation Through Learning Rate and Momentum Adaption ”, in International Joint Conference on Neural Networks, IEEE, pp 676-679, 1990.
- Shuiwang Ji, and Jieping Ye, ,“ Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection”, in IEEE transactions on Neural Networks, Vol. 19, No. 10, October 2008
- Dong Xu, Yi Huang, Zinan Zeng and Xinxing Xu, ,“ Human Gait Recognition Using Patch Distribution Feature and Locality-Constrained Group Sparse Representation ”, in IEEE Transactions on Image Processing, Vol. 21, No. 1, January 2012.
- Deng Cai, Xiaofei He, and Jiawei Han, ,“ SRDA An Efficient Algorithm for Large-Scale Discriminant Analysis”, in IEEE transactions on knowledge and Data Engineering, Vol. 20, No. 1, January 2008
- Shuicheng Yan, Dong Xu, Qiang Yang Lei Zhang Xiaoou Tang and Hong-Jiang Zhang, ,“ Multilinear Discriminant Analysis for face recognition”,in IEEE Transactions on Image Processing, Vol.16, No. 1 January 2007.
- Tao.Li, Shenghuo.Zhu, and Mitsunori. Ogihara, ,“ Using discriminant for multi-class classification: an experimental investigation ”,In Knowledge and Information Systems, Vol. 10, pp453-472, 2006.
Index Terms
Keywords