A Novel GAIT Classification Approach Using ELM
Abstract
Keywords
Full Text:
PDFReferences
Simon S. R., Quantification of human motion: gait analysis-benefits and limitations to its application to clinical problems. Journal of Biomechanics, 2004(37): 1869-1880.
Barton J G, Lees A, An application of neural networks for distinguishing gait patterns on the basis of hip-knee joint angle diagrams. Gait and Posture, 1997(5): 28-33.
R. K. Begg, M. Palaniswami, and B. Owen, Support Vector Machines for automated gait classification. IEEE Trans. Biomed. Eng., vol. 52, no. 5, pp. 828-823, May 2005.
Joarder Kamruzzaman, Support Vector Machines and Other Pattern Recognition Approaches to the Diagnosis of Cerebral Palsy Gait. IEEE Trans. Biomed. Eng., vol. 53, no. 12, pp. 2479-2489, Dec 2006.
A. Bobick and W. Davis. The recognition of human movement using temporal templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(3),March 2001.
Ross Cutler and Larry Davis. Robust real-time periodic motion detection, analysis, and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):781 –796, 2000.
Sheng-Wu Xiong, Hong-Bing Liu and Xiao-Xiao Niu, Fuzzy support vector machines based on FCM clustering. Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Aug. 2005, vol. 5, pp. 2608- 2613.
G.-B. Huang, Q.-Y. Zhou, and CK. Siew, “Extreme Learning Machine: A New Learning Scheme of Feedforward Neural Networks,” Proc. Int’l Joint Conf. Neural Networks (IJCNN ’04), July 2004.
G.-B. Huang and C.-K. Siew, “Extreme Learning Machine with Randomly Assigned RBF Kernels,” Int’l J. Information Technology, vol. 11, no. 1, 2005.
Vladimir N. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995, 187 pp.
Dunn and J.C., Some recent investigations of a new fuzzy partition algorithm and its application to pattern classification problems. J. Cybernetics, vol. 4, pp. 1–15, 1974.
Bezdek and J.C., Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum, New York, 1981.
X. Wang, Y. Wang, and L. Wang, Improving Fuzzy c-Means Clustering based on Feature-Weight Learning. Pattern Recognition Letters, 25 (10), pp. 1123–1132, 2004.
Dae-Jong Lee, Jong-Pil Lee, Pyeong-Shik Ji, Jae-Woon Park and Jae-Yoon Lim, Fault Diagnosis of Power Transformer Using SVM and FCM. 2008 IEEE International Symposium on Electrical Insulation, June 2008, pp. 112-115.
G.-B. Huang, “Learning Capability and Storage Capacity of Two- Hidden-Layer Feedforward Networks,” IEEE Trans. Neural Networks, vol. 14, no. 2, pp. 274-281, 2003.
Ju Han, Bir Bhanu, "Individual Recognition Using Gait Energy Image", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 2, February 2006.
Davrondzhon Gafurov, "A Survey of Biometric Gait Recognition: Approaches, Security and Challenges", NIK-2007 conference.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.