Abstract
Human identification in a distance by the analysis of gait patterns extracted from video has recently become a research topic. In this paper, a feature fusion method is proposed for gait recognition. Firstly, four energy accumulation images of gait energy image (GEI), change energy images (CIE), are generated from a sequence of silhouettes of a gait cycle. Secondly, Orthogonal locally discriminant projection (OLDP) is applied to four sequence of energy accumulation images and four low-dimensionality vectors are obtained, respectively. Thirdly, the classifying feature vector is established by fusing the four vectors. Then nearest neighbor criterion is employed to recognize gait. The experimental results on Chinese CASIA database A show the effectiveness and feasibility of the method proposed in this paper.
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References
Yu, S., Tan, T., Huang, K., et al.: A Study on Gait-Based Gender Classification. IEEE Transactions on image processing 18(2), 1905–1910 (2009)
Tanawongsuwan, R., Bobick, A.: Modeling the effects of walking speed on appearance based gait recognition. In: Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004), vol. 2, pp. 783–790 (2004)
Ben Abdelkader, C., Culter, R., Davis, L.: Stride and cadence as a biometric in automatic person identification and verification. In: Proc. Int. Conf. Automatic Face and Gesture Recognition, Washington, pp. 372–376 (2002)
Tao, D., Li, X., Wu, X., Maybank, S.J.: General tensor discriminant analysis and gabor features for gait recognition. IEEE Trans. Pattern Anal. Mach. Intell. 29(10), 1700–1715 (2007)
Matovski, D., Nixon, M., Mahmoodi, S., et al.: The Effect of Time on Gait Recognition Performance. IEEE Trans. on Info. Forensics and Security 7(2), 543–552 (2012)
Han, J., Bhanu, B.: Individual recognition using gait energy image. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(2), 316–322 (2006)
Ali, H., Dargham, J., Ali, C., et al.: Gait Recognition using Gait Energy Image. International Journal of Signal Processing, Image Processing and Pattern Recognition 4(3), 141–152 (2011)
Lee, H., Hong, S., Kim, E.: An Efficient Gait Recognition with Backpack Removal. Hindawi Publishing Corp. EURASIP Journal on Advances in Signal Processing 1, 1–7 (2009)
Wang, L., Tan, T., Hu, W., Ning, H.: Silhouette Analysis-Based Gait Recognition for Human Identification. IEEE Trans. on Pattern Analysis and Machine Intelligence 25(12), 1505–1518 (2003)
Amin, T., Hatzinakos, W.: Determinants in Human Gait Recognition. Journal of Information Security 3, 77–85 (2012)
Hong, S., Lee, H., Nizami, I.F., Kim, E.: A new gait representation for human identification: mass vector. In: Proc. IEEE Conference on Industrial Electronics and Applications, pp. 669–673 (2007)
Cheng, Q., Fu, B., Chen, H.: Gait recognition based on PCA and LDA. In: Proceedings of the Second Symposium International Computer Science and Computational Technology, Huanshan, China, pp. 124–127 (2006)
Okumura, M., Iwama, H., Makihara, Y., et al: Performance evaluation of vision-based gait recognition using a very large-scale gait database. In: Fourth IEEE International Conference Biometrics: Theory Applications and Systems (BTAS), pp. 1–6 (2010)
Xu, D., Yan, S., Tao, D., et al.: Marginal Fisher Analysis and Its Variants for Human Gait Recognition and Content- Based Image Retrieval. IEEE Transactions on Image Processing 16(11), 2811–2821 (2007)
Wu, J.: Automated recognition of human gait pattern using manifold learning algorithm. In: 2012 8th International Conference on Natural Computation (ICNC 2012), pp. 199–202 (2012)
Wang, L., Tan, T.N., Hu, W.M., Ning, H.Z.: Automatic Gait Recognition Based on Statistical Shape Analysis. IEEE Transactions on Image Processing 12(9), 1120–1129 (2003)
Ali, H., Jamal, D., Ali, C., Moung, E.G.: Gait Recognition using Gait Energy Image. International Journal of Signal Processing, Image Processing and Pattern Recognition 4(3), 141–152 (2011)
Chen, J., Liu, J.: Average Gait Differential Image Based Human Recognition. Hindawi Publishing Corporation e Scientific World Journal, 8 (2014)
Zhang, J., Pu, J., Chen, C., Fleischer, R.: Low-resolution gait recognition. IEEE Trans. Syst. Man Cybern B Cybern. 40(4), 986–996 (2010)
Wang, F., Zhang, C.: Feature extraction by maximizing the average neighborhood margin. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8 (2007)
Zhang, S.W., Lei, Y.K., Wu, Y.H., et al.: Modified orthogonal discriminant projection for classification. Neurocomputing 74(17), 3690–3694 (2011)
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Zhang, C., Zhang, S., Yang, J., Cheng, W. (2015). Gait Recognition Based on Energy Accumulation Images. In: Yang, J., Yang, J., Sun, Z., Shan, S., Zheng, W., Feng, J. (eds) Biometric Recognition. CCBR 2015. Lecture Notes in Computer Science(), vol 9428. Springer, Cham. https://doi.org/10.1007/978-3-319-25417-3_54
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DOI: https://doi.org/10.1007/978-3-319-25417-3_54
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