Contents & References of Combining body movement information and foot contact forces to recognize human identity by analyzing walking method
List:
Table of Contents
Chapter One: Research Overview
Introduction
Problem Statement
Research Hypotheses
1-3-1 Overview of Biometric History
Chapter Two: Theoretical Foundations and Research Background
Methods for identifying people from Information
2-1-1- Identity recognition through fingerprint
2-1-2- Identity recognition through eyes
2-1-3- Identity recognition through face
2-1-4- Identity recognition Identity through speech
2-1-5- Identity recognition through signature
Identifying people through walking
2-2-1- Model-based method
2-2-2- Appearance-based method
Chapter three: Materials and methods
1-3-Collection Data
3-3-1- Schematic model
3-1-2- How SPI sensor works
3-2- Feature extraction
3-2-1- Measurement of variables
3-2-2- Number of variables
3-2-3 Statistical population
3-3- Classification
3-3-1- Neural networks Artificial
3-3-2-Perceptron learning algorithm
3-3-3-Neural network design in MATLAB
Chapter four
Identity recognition with trained network
Conclusion
Future work
Resources
List of tables
Page
3-1 Obtained data A
38
3-2 Validation data
39
3-3 Obtained data B
443-4 Evaluation data
4-1 Network output per rows of table 3-2
Source:
[1] M. Bamberg, S. James. "Gait analysis using a shoe-integrated wireless sensor system." Information Technology in Biomedicine, IEEE Transactions on 12.4 (2008): 413-423. [2] Yu, Hui. "A walking monitoring shoe system for simultaneous plantar-force measurement and gait-phase detection." Advanced Intelligent Mechatronics (AIM), 2010 IEEE/ASME International Conference on. IEEE, 2010. [3Rong.Z, Vogler.C, and Metaxas.D. "Human gait recognition." Computer Vision and Pattern Recognition Workshop, 2004. CVPRW'04. Conference on. IEEE, 2004. [4] Liang.w. "Fusion of static and dynamic body biometrics for gait recognition." Circuits and Systems for Video Technology, IEEE Transactions on 14.2 (2004): 149-158. "Model-based human gait recognition using leg and arm movements." Engineering applications of artificial intelligence 23.8 (2010): 1237-1246. [6] Davrondzhon.g. "A survey of biometric gait recognition: Approaches, security and challenges." Annual Norwegian Computer Science Conference. 2007.
[7] Chan-Su L, Elgammal.A, Gait Style and Gait Content: Bilinear Models for Gait Recognition Using Gait Re-sampling, 2010.
[8] Behnaz Abdolahi and Nilofar Qaysari, Human identification based on the way of walking with the help of dynamic texture descriptor, intelligent systems in electrical engineering, fourth year, Issue Two, Summer 92
[9] Moustakas. K, Tzovaras.D, and Stavropoulos.G. "Gait recognition using geometric features and soft biometrics." Signal Processing Letters, IEEE 17.4 (2010): 367-370. [10] Sudha, L. R., and Dr. Rao. Bhavani. "Biometric Authorization System using Gait Biometry." arXiv preprint arXiv:1108.6294 (2011).
.
[11] Weijun.T., "Gait analysis using wearable sensors." Sensors 12.2 (2012): 2255-2283.
[12] Ali Amiri, Mahmoud Fathi, Rauf Taheri, Presenting a new approach to recognize the identity of people from walking based on the modified DTW algorithm and fuzzy sets 26 Bahman 1385
[13] Hafner.V, and Bachmann.F. "Human-humanoid walking gait recognition." Humanoid Robots, 2008. Humanoids 2008. 8th IEEE-RAS International Conference on. IEEE, 2008.
[14] Ju.H and Bhanu.B,” Individual Recognition Using Gait Energy Image,” PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 28, NO. 2, FEBRUARY
[15] Ali Amiri, Mahmoud Fathi, Kamal Kayani, Nasim Homayouni, "identification of people from walking based on clustering algorithm based on genetic algorithms and modified DTW algorithm," 12th International Conference of the Iranian Computer Association, Shahid Beheshti University, Faculty of Electrical and Computer Engineering, Tehran, Iran, 1 to 3 Isfand 13
[16] Liang.W., "Silhouette analysis-based gait recognition for human identification." Pattern Analysis and Machine Intelligence, IEEE Transactions on 25.12 (2003): 1505-1518.
[17] Shervin Rahimzadeh Arashlo, Alireza Ahmadifard and Hossein Maravi, "Individual identification using time and frequency domain features from walking model," Fuzzy Systems Association of Ferdowsi University of Mashhad, August 29-31, 2007.
[18] Gholamreza Chamankhah, Saeed Meshghini, "Providing an optimal method for recognizing the identity of people through walking biometrics," 9th Iran International Cipher Conference, September 2013.
[19] Muzhir Sh. Al-Ani, Isra H. Al-Ani "Gait Recognition Based Improved Histogram", Journal of Emerging Trends in Computing and Information Sciences, VOL. 2, NO. 12, December 2011.
[20] Félez.M, R, and Xiang.T., "Gait recognition by ranking." Computer Vision–ECCV 2012. Springer Berlin Heidelberg, 2012. 328-341.
[21] Mahdia Karimi Lakhani, Hamid Behnam, "Identifying people from the way they walk using an algorithm", LLE Journal of Electrical Engineering of Tabriz University, Volume 43, Vol. 43, No. 1, 2012
[22] Esmail Ebrahimi, Hassan Saeedi, "Investigation of leg pressure distribution during walking in adults," Rehabilitation research paper, 10th edition, issue 2, serial number 38, summer 88
[23] Katiyar.R, K.P.Vinay, K.V. Arya, "A Study on Existing Gait Biometrics Approaches and Challenges," International Journal of Computer Science Issues, January 2013, Vol. 10, Issue 1, No 1.
[ 24]A. Kale, A.N. Rajagopalan, N. Cuntoor1 and V Kr¨uger, "Gait-based Recognition of Humans Using Continuous HMMs," Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition (FGR.02), 2002.
[25] Tie.C, K Ong Goh.M, Beng Jin Teoh.A "Gait Analysis and Recognition Using Multi-Views Gait Database." International Journal of Digital Information and Wireless Communications (IJDIWC) 1.2 (2011): 466-478.
[26] Phillips, P. Jonathon,. "The gait identification challenge problem: data sets and baseline algorithm." Pattern Recognition, 2002. Proceedings. 16th International Conference on Vol. 1. IEEE, 2002.