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GAIT Recognition using PAL and PAL Entropy with BPNN, SVM and MDA
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 120 - Number 12 |
| Year of Publication: 2015 |
| Authors: Lateshwari, Pooja Kaplesh |
10.5120/21282-4208
|
Lateshwari, Pooja Kaplesh . GAIT Recognition using PAL and PAL Entropy with BPNN, SVM and MDA. International Journal of Computer Applications. 120, 12 ( June 2015), 33-35. DOI=10.5120/21282-4208
Abstract
Gait recognition is one sort of biometric innovation that can be utilized to monitor individuals without their collaboration. Controlled situations for example banks, army bases and even terminals need to have the capacity to rapidly distinguish dangers and give varying levels of access to distinctive client groups. Gait demonstrates a specific way or way of proceeding onward foot and gait recognition is the procedure of distinguishing a person by the way in which they walk. Gait is less unpretentious biometric which offers the likelihood to distinguish individuals at a distance with no connection or co-operation from the subject and this is the property which makes it so engaging. This paper proposed new system for gait recognition. In this method, firstly binary silhouette of a walking person is detected from each frame. Secondly, feature from each frame is extracted using image processing operation. Here step size length, distance between hands and cycle length are talking as key feature. Here all experiments are done on gait database. Different groups of training and testing dataset give different results.
References
- Jeevan, M. , et al. "Indian Institute of Technology Delhi, India. " Image Processing (ICIP), 2013 20th IEEE International Conference on. IEEE, 2013.
- Alese, B. K. , et al. "Design and Implementation of Gait Recognition System. " International Journal of Engineering and Technology 2. 7 (2012): 1102-1110.
- Bharti, Jyoti, and M. K. Gupta. "Gait recognition with geometric characteristic and fuzzy logic. " Canadian Journal on Image Processing and Computer Vision 3. 1 (2012): 6-11.
- Hayder, A. , et al. "Person Identification Using Gait. " International Journal of Computer and Electrical Engineering 3. 4 (2011): 477-482.
- Sharma, Sanjeev, et al. "Identification of People Using Gait Biometrics. " International journal of machine learning and computing 1. 4 (2011): 409-415.
- Liu, Lili, et al. "Gait recognition based on outermost contour. " International Journal of Computational Intelligence Systems 4. 5 (2011): 1090-1099.
- N. K Narayanan,V. Kabeer, "Face recognition using nonlinear feature parameter and artificial neural network," International journal of computer intelligence systems, 3(5), 566-574.
- 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
- S. J. McKenna, S. Jabri, Z. Duric, "Tracking group of people," Comput. Vis. Image Understanding, vol. 80, no. 1,pp. 42-56
- Davrondzhon Gafurov, Einar Snekkenes and Patrick Bour, "Improves gait recognition performance using cycle matching", International conference on Advanced Information Networking and Applications, Perth, Australia, 20-23 April 2010.
- Ali, Hayder, et al. "Gait Recognition using Principal Component Analysis. " Proceedings of the 3rd International Conference onMachine Vision. 2010.
- Agarwal, Shalini, and Shaili Mishra. "A Study of multiple human tracking for visual surveillance. " International Journal 5 (1963).
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