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Conf. on Pattern Recognit., pp.741-744, 2004. 10.1109\/ICPR.2004.1333879","DOI":"10.1109\/ICPR.2004.1333879"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[6] J. Han and B. Bhanu, \u201cIndividual recognition using gait energy image,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.28, no.2, pp.316-322, Feb. 2006. 10.1109\/TPAMI.2006.38","DOI":"10.1109\/TPAMI.2006.38"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[7] Y. Makihara, R. Sagawa, Y. Mukaigawa, T. Echigo, and Y. Yagi, \u201cGait recognition using a view transformation model in the frequency domain,\u201d Proc. ECCV, Lect. Notes Comput. Sci., vol.3953, pp.151-163, Springer, 2006. 10.1007\/11744078_12","DOI":"10.1007\/11744078_12"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[8] K. Bashir, T. Xiang, and S. Gong, \u201cGait recognition using gait entropy image,\u201d Proc. the 3rd Int. 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Liu, \u201cGait flow image: A silhouette-based gait representation for human identification,\u201d Pattern Recognit., vol.44, no.4, pp.973-987, April 2011. 10.1016\/j.patcog.2010.10.011","DOI":"10.1016\/j.patcog.2010.10.011"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[12] T. Bouwmans, F. Porikli, B. H\u00f6ferlin, and A. Vacavant, Background modeling and foreground detection for video surveillance, CRC press, 2014.","DOI":"10.1201\/b17223"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[13] D.S. Lee, \u201cEffective gaussian mixture learning for video background subtraction,\u201d IEEE Trans. Pattern Analysis & Machine Intelligence, vol.27, no.5, pp.827-832, May 2005. 10.1109\/TPAMI.2005.102","DOI":"10.1109\/TPAMI.2005.102"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[15] C. Rother, V. Kolmogorov, and A. Blake, \u201cGrabCut: Interactive foreground extraction using iterated graph cuts,\u201d ACM Trans. Graph., vol.23, no.3, pp.309-314, Aug. 2004. 10.1145\/1015706.1015720","DOI":"10.1145\/1015706.1015720"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[16] Z. Gao, P. Shi, H.R. Karimi, and Z. Pei, \u201cA mutual grabcut method to solve co-segmentation,\u201d EURASIP J. Image and Video Processing, vol.2013, no.1, p.20, 2013. 10.1186\/1687-5281-2013-20","DOI":"10.1186\/1687-5281-2013-20"},{"key":"15","doi-asserted-by":"publisher","unstructured":"[17] A. Levin, D. Lischinski, and Y. Weiss, \u201cA closed-form solution to natural image matting,\u201d Proc. IEEE Computer Society Conf. Comput. Vis. Pattern Recognit. (CVPR), pp.228-242, Feb. 2008. 10.1109\/TPAMI.2007.1177","DOI":"10.1109\/TPAMI.2007.1177"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[18] M. Hofmann, S.M. Schmidt, A. Rajagopalan, and G. Rigoll, \u201cCombined face and gait recognition using alpha matte preprocessing,\u201d Proc. the 5th IAPR Int. 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Robotics and Automation, pp.1698-1703, 2008. 10.1109\/ROBOT.2008.4543445"},{"key":"20","doi-asserted-by":"publisher","unstructured":"[22] Y. Makihara, T. Tanoue, D. Muramatsu, Y. Yagi, S. Mori, Y. Utsumi, M. Iwamura, and K. Kise, \u201cIndividuality-preserving silhouette extraction for gait recognition,\u201d IPSJ Trans. Comput. Vis. and Applications, vol.7, pp.74-78, 2015. 10.2197\/ipsjtcva.7.74","DOI":"10.2197\/ipsjtcva.7.74"},{"key":"21","doi-asserted-by":"publisher","unstructured":"[23] H. Iwama, M. Okumura, Y. Makihara, and Y. Yagi, \u201cThe OU-ISIR gait database comprising the large population dataset and performance evaluation of gait recognition,\u201d IEEE Trans. Inf. Forensics Security, vol.7, no.5, pp.1511-1521, Oct. 2012. 10.1109\/TIFS.2012.2204253","DOI":"10.1109\/TIFS.2012.2204253"},{"key":"22","doi-asserted-by":"publisher","unstructured":"[24] N. Dalal and B. Triggs, \u201cHistograms of oriented gradients for human detection,\u201d Proc. IEEE Computer Society Conf. 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