Human gait identification using Kinect sensor

Abstract = 3 times | PDF = 75 times

Main Article Content

Azhin Tahir Sabir Mohammed H. Ahmed Abdulbasit K. Faeq Halgurd S. Maghdid

Abstract

This study investigates a novel three-dimension gait recognition approach based on skeleton representation of motion by the cheap consumer level camera Kinect sensor. In this work, a new exemplification of human gait signature is proposed using the spatio-temporal variations in relative angles among various skeletal joints and changing of measured distance between limbs and land. These measurements are computed during one gait cycle. Further, we have created our own dataset based on Kinect sensor and extract two sets of dynamic features. Nearest Neighbors and Linear Discriminant Classifier (LDC) are used for classification. The results of the experiments show the proposed approach as an effective and human gait recognizer in comparison with current Kinect-based gait recognition methods.

Downloads

Download data is not yet available.

Article Details

References

[1] J. Preis, M. Kessel, M. Werner, and C. Linnhoff-Popien, "Gait recognition with kinect," in 1st international workshop on kinect in pervasive computing, 2012, pp. P1-P4.
[2] R. Das, "An introduction to biometrics," Military Technology, vol. 29, pp. 20-27, 2005.
[3] M. Kumar and R. V. Babu, "Human gait recognition using depth camera: a covariance based approach," in Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing, 2012, p. 20.
[4] A. Jana, Kinect for windows SDK programming guide: Packt Publishing Ltd, 2012.
[5] J. P. Singh and S. Jain, "Person identification based on gait using dynamic body parameters," in Trendz in Information Sciences & Computing (TISC), 2010, 2010, pp. 248-252.
[6] A. K. Jhapate and J. P. Singh, "Gait Based Human Recognition System using Single Triangle," International Journal of Computer Science and Technology, pp. 128-131, 2011.
[7] J. Han and B. Bhanu, "Statistical feature fusion for gait-based human recognition," in Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, 2004, pp. II-II.
[8] J. Wang, M. She, S. Nahavandi, and A. Kouzani, "A review of vision-based gait recognition methods for human identification," in Digital Image Computing: Techniques and Applications (DICTA), 2010 International Conference on, 2010, pp. 320-327.
[9] C. BenAbdelkader, R. Cutler, and L. Davis, "Stride and cadence as a biometric in automatic person identification and verification," in Automatic Face and Gesture Recognition, 2002. Proceedings. Fifth IEEE International Conference on, 2002, pp. 372-377.
[10] R. Urtasun and P. Fua, "3D tracking for gait characterization and recognition," in Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on, 2004, pp. 17-22.
[11] C. Yam, M. S. Nixon, and J. N. Carter, "Automated person recognition by walking and running via model-based approaches," Pattern Recognition, vol. 37, pp. 1057-1072, 2004.
[12] A. Sinha, K. Chakravarty, and B. Bhowmick, "Person identification using skeleton information from kinect," in Proc. Intl. Conf. on Advances in Computer-Human Interactions, 2013, pp. 101-108.
[13] J. Man and B. Bhanu, "Individual recognition using gait energy image," IEEE transactions on pattern analysis and machine intelligence, vol. 28, pp. 316-322, 2006.
[14] A. F. Bobick and J. W. Davis, "The recognition of human movement using temporal templates," IEEE transactions on pattern analysis and machine intelligence, vol. 23, pp. 257-267, 2001.
[15] C. Chen, J. Liang, H. Zhao, H. Hu, and J. Tian, "Frame difference energy image for gait recognition with incomplete silhouettes," Pattern Recognition Letters, vol. 30, pp. 977-984, 2009.
[16] X. Li and Y. Chen, "Gait recognition based on structural gait energy image," Journal of Computational Information Systems, vol. 9, pp. 121-126, 2013.
[17] J. Shotton, T. Sharp, A. Kipman, A. Fitzgibbon, M. Finocchio, A. Blake, M. Cook, and R. Moore, "Real-time human pose recognition in parts from single depth images," Communications of the ACM, vol. 56, pp. 116-124, 2013.
[18] E. E. Stone and M. Skubic, "Evaluation of an inexpensive depth camera for passive in-home fall risk assessment," in Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2011 5th International Conference on, 2011, pp. 71-77.
[19] Y.-J. Chang, S.-F. Chen, and J.-D. Huang, "A Kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities," Research in developmental disabilities, vol. 32, pp. 2566-2570, 2011.
[20] M. Popa, A. K. Koc, L. J. Rothkrantz, C. Shan, and P. Wiggers, "Kinect sensing of shopping related actions," in International Joint Conference on Ambient Intelligence, 2011, pp. 91-100.
[21] A. Ball, D. Rye, F. Ramos, and M. Velonaki, "Unsupervised clustering of people from'skeleton'data," in Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction, 2012, pp. 225-226.
[22] M. Gabel, R. Gilad-Bachrach, E. Renshaw, and A. Schuster, "Full body gait analysis with Kinect," in Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, 2012, pp. 1964-1967.
[23] M. H. Ahmed and A. T. Sabir, "Human Gender Classification Based on Gait Features Using Kinect Sensor," in Cybernetics (CYBCONF), 2017 3rd IEEE International Conference on, 2017, pp. 1-5.
[24] A. Sabir, N. Al-jawad, and S. Jassim, "Gait recognition using spatio-temporal silhouette-based features," in Proc. of SPIE Vol, 2013, pp. 87550R-1.
[25] M. H. Ahmed, "Kinect-Based Human Gait Recognition Using Static and Dynamic Features," International Journal of Computer Science and Information Security, vol. 14, p. 425, 2016.