Passive people Identification using video footage of them walking

Document Type : Original Article

Authors

, Islamic Azad University, Damavand

Abstract

Now , gait recognition is one of the biometric methods that has received more and more attention researchers in machine vision and pattern recognition. However, one of the main challenges of technology is variations caused by covariate factors such as fast and slow gait, clothing, carrying conditions.this reserch tried is to provide issues in three basic parts: preprocessing, feature extraction, and classification. Using the Cassia data set, which is a large set with different gestures and carrying conditions. First, organized a new Spatio-temporal database with horizontal profiling of the silhouette. next, feature extracting by PCA. Finally, the SVM algorithm is used and classifies and identifies. The test results show the efficiency of the proposed algorithm under different conditions.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Keywords


Smiley face

   [1]      M. Gomez-Barrero, C. Rathgeb, G. Li, R. Ramachandra, J. Galbally, and C. Busch,  “Multi-biometric template protection based on bloom filters,” Information Fusion, vol. 42, no. 1, pp. 37-50, 2018.##
   [2]      P. H. Pisani, N. Poh, A. C. De Carvalho, and A. C. Lorena, “Score normalization applied to adaptive biometric systems,” Computers & Security, vol. 70, no. 1, pp. 565-580, 2017.##
   [3]      S. Wang and A. W. Liew, “Physiological and behavioral lip biometrics: A comprehensive study of their discriminative power,” Pattern Recognition, vol. 45, no. 9, pp. 3328-3335, 2012.##
   [4]      U. Saeed, “Eye movements during scene understanding for biometric identification,” Pattern Recognition Letters, vol. 82, no. 1, pp. 190-195, 2016.##
   [5]      K. O. Bailey, J. S. Okolica, and G. L. Peterson, “User identification and authentication using     multi-modal behavioral biometrics,” Computers & Security, vol. 43, no. 1, pp. 77-89, 2014.##
   [6]      P. Connor and A. Ross, “Biometric recognition by gait: A survey of modalities and features, Computer Vision and Image A survey on gait recognition,” ACM Computing Surveys, vol. 51, no. 5, pp. 1–35, 2018.##
   [7]      C. Wan, L. Wang, and V. V. Phoha, “survey on gait recognition,” ACM Computing Surveys, vol. 51, no. 5, pp. 1–35, 2018.##
   [8]      Z. Wu, Y. Huang, L. Wang, X. Wang, and T. Tan, “A comprehensive study on cross-view gait based human identification with deep CNNs,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 02, pp. 209–226, 2017.##
   [9]      I. Rida, N. Noor Almaadeed, and S. Al-ma'adeed, “Robust gait recognition: a comprehensive survey,” IET Biometrics journal, vol. 8, Issue 1, pp. 14 - 28, 2019.##
[10]      Y. Hirose, K. Nakamura, N. Nitta, and N. Babaguchi, “Anonymization of Gait Silhouette Video by Perturbing Its Phase and Shape Components,” APSIPA ASC Conference, Lanzhou, China, pp. 1679-1685, 2019.##
[11]      B. Jawed, O. O. Khalifa, and S. S. Newaj Bhuiyan, “Human Gait Recognition System,” 2018 7th International Conference on Computer and Communication Engineering (ICCCE), Kuala Lumpur, pp. 89-92, 2018.##
[12]      K. Bashir, T. Xiang, and S. Gong, “Gait recognition using gait entropy image,” in Proc. 3rd Int. Conf. Crime Detect. Prevention, pp. 1–6, 2009.##
[13]      X. Yang, Y. Zhou, T. Zhang, G. Shu, and J. Yang, “Gait recognition based on dynamic region analysis,” Signal Process, vol. 88, pp. 2350–2356, 2008.##
[14]      E. Zhang, Y. Zhao, and W. Xiong, “Active energy image plus 2dlpp for gait recognition,” Signal Process, vol. 90, no. 7, pp. 2295–2302, 2010.##
[15]      K. Bashir, T. Xiang, and S. Gong, “Gait recognition without subject cooperation,” Pattern Recognit. Lett., vol. 31, no. 13, pp. 2052–2060, 2010.##
[16]      K. Bashir, T. Xiang, and S. Gong, “Gait representation using flow fields,” in Proc. Brit. Mach. Vis. Conf., pp. 1–11, 2009.##
[17]      P. Chaurasia, P. Yogarajah, J. Condell, and G. S. Prasad, “Fusion of Random Walk and Discrete Fourier Spectrum Methods for Gait Recognition,” IEEE Transactions on Human-Machine Systems, vol. 47 , Issue. 6 , Dec. 2017.##
[18]      M. Jeevan, N. Jain, M. Hanmandlu, and G. Chetty, “Gait recognition based on gait pal and pal entropy image,” IEEE International Conference on Image Processing, Melbourne, VIC, pp. 4195-4199, 2013.##
[19]      J. Rouhi and H. Sadoughi, “Presenting a new    spatio-temporal database on the gait and using to recognition people from video images,” in Proc. 12th conference of the Iranian Computer Association, 2006. (In Persian)##
[20]      M. Hu, Y. Wang, Z. Zhang, D. Zhang, and J. J. Little, “Incremental Learning for Video-Based Gait Recognition With LBP Flow,” IEEE Transactions on Cybernetics, vol. 43, no. 1, pp. 77-89, Feb. 2013.##
[21]      S. Yu, D. Tan, and T. Tan, “A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition,” in Proc. 18th Int. Conf. Pattern Recog, pp. 441–444, 2006.##
Y. Pratheepan, J. Condell, and G. Prasad, “PRWGEI: Poisson random walk based gait recognition,” in Proc. 7th Int. Symp. Image Signal Process. Anal., pp. 662–667, 2011.##