International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 6, No. 4, 8 Mar. 2014
Cover page and Table of Contents: PDF (size: 362KB)
Change Energy Image for Gait Recognition: An Approach Based on Symbolic Representation
Full Text (PDF, 362KB), PP.1-8
Views: 0 Downloads: 0
Author(s)
Index Terms
Change energy images, interval valued features, subject (individual person), Radon transform, representation, similarity measure
Abstract
Gait can be identified by observing static and dynamic parts of human body. In this paper a variant of gait energy image called change energy images (CEI) are generated to capture detailed static and dynamic information of human gait. Radon transform is applied to CEI in four different directions (vertical, horizontal and two opposite cross sections) considering four different angles to compute discriminative feature values. The extracted features are represented in the form of interval –valued type symbolic data. The proposed method is capable of recognizing an individual when he/she have variations in their gait due to different clothes they wear, in different normal conditions and carrying a bag. A similarity measure suitable for the proposed gait representation is explored for the purpose of establishing similarity match for gait recognition. Experiments are conducted on CASIA database B and the results have shown better recognition performance compared to some of the existing methods.
Cite This Paper
Mohan Kumar H P, Nagendraswamy H S,"Change Energy Image for Gait Recognition: An Approach Based on Symbolic Representation", IJIGSP, vol.6, no.4, pp.1-8, 2014. DOI: 10.5815/ijigsp.2014.04.01
Reference
[1]Xuelong Li, Stephen J.Maybank, Shuicheng Yan, Dacheng Tao and Dong Xu, "Gait components and their Application to Gender Recognition", IEEE Trans on Systems, Man and Cybernetics- part C: Aplications and Review, Vol. 38, no. 2, March 2008.
[2]Zongyi Liu, Laura Malave, Adebola Osuntugun, Preksha Sudhakar and Sudeep Sarkar, " Towards Understanding the limts of Gait Recognition", SPIE International Symposium on Defense and Security: Biometric Technology for Human Identification, April 2004.
[3]Haiping Lu, Konstantinos N.Plataniotis and Anastasios N.Venetsanopoulos, "A Full-Body Layered Deformable Model for Automatic Model-Based Gait Recognition", EURASIP Journal on Advances in Signal Processing, Volume 2008, Article ID 261317.
[4]Rong Zhang, Christian Vogler and Dimitris Metaxas, "Human Gait Recognition", Conference on Computer Vision and Pattern Recognition Workshops (CVPRW'04), 106-6919/04 IEEE.
[5]Nikolaos V.Boulgouris, Dimitrois Hatzinakos and Konstantinos N. Plataniotis, "Gait Recognition: A Challenging signal processing technology for biometric identification", IEEE Signal Processing Magazine page 78-90 November 2005.
[6]Mridul Ghosh and Debotosh Bhattacharjee, "Human Identification by using corner points", International journal of Graphics and Signal processing, 2012, 2, 30-36.
[7]Ju Han and Bir Bhanu, "Individual Recognition using Gait Energy Image", IEEE Transactions on Pattern analysis and Machine Intelligence, VOL 28, NO 2, February 2006.
[8]Xiaoxiang LI and Youbin CHEN, "Gait Recognition based on structural Gait Energy Image", Journal of Computational Information Systems 9:1 (2013) 121-126.
[9]Yumi Iwashita, Adrian Stoica and Ryo Kurazume, "Gait identification using shadow biometrics", Pattern Recognition Letters 33 (2012) 2148-2155.
[10]Toby H W Lam, Raymond S T Lee and David Zhang, "Human gait recognition by the fusion of motion and static spatio-temporal templates", Pattern Recognition 40 (2007) 2563-2573.
[11]Nikolaos V Boulgouris and Zhiwei X Chi, "Human gait Recognition based on matching body components", Pattern Recognition 40 (2007) 1763-1770.
[12]Sudeep Sarkar, P. Jonathon Philips, Zongyi Liu, Isidro Robledo Vega, Patrick Grother and Kevin W. Bowyer, "The HumanID Gait Challenge Problem: Data sets, Performance, and Analysis ", IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 27, no.2, February 2005.
[13]Amit Kale, Aravind Sundaresan, A.N.Rajagopaln, Naresh P.Cuntoor,Amit K. Roy-chowdhury,
Volker Kruger and Rama Chellappa, "Identification of Humans Using Gait", IEEE Trans on Image Processing, Vol.13, no.9, September 2004.
[14]K.C.Gowda and E.Diday, "Symbolic clustering using a new dissimilarity measure," Pattern Recognition 24(6), 567-578 (1991).
[15]D.S.Guru, B.B.Kiranagi and P.Nagabhushan, " Multivalued type proximity measure and concept of mutual similarity value useful for clustering symbolic patterns,". Pattern Recognition Letters 25(10), 1203-1213 (2004).
[16]S.Guru, and B.B.Kiranagi, " Multivalued type dissimilarity measure and concept of mutual dissimilarity value useful for clustering symbolic patterns," Pattern Recognition 38(1), 151-156 (2005).
[17]K.C.Gowda and E.Diday, "Symbolic clustering using a new similarity measure," IEEE Trans. SMC 22(2), 368-378 (1992).
[18]K.C.Gowda and T.V.Ravi, "Agglomerative clustering of symbolic objects using the concepts of both similarity and dissimilarity," Pattern Recognition Letters 16, 647-652 (1995a).
[19]K.C.Gowda and T.V.Ravi, "Divisive clustering of symbolic objects using the concepts of both similarity and dissimilarity," Pattern Recognition Letters 28(8), 1277-1282 (1995b).
[20]M.Ichino and H.Yaguchi, "Generalized Minkowski metrices for mixed feature type data analysis," IEEE Trans on system, Man and Cybernetics 24(4), (1994).
[21]T.Denoeux and M.Masson, "Mutidimensional scaling of interval valued dissimilarity data, " Pattern Recognition Letters 21, 83-92 (2000).
[22]A.K.Jain and R.C.Dubes, "Algorithms for clustering data," Prentice Hall, Englewood Cliffs (1988).
[23]Guru D S and Nagendraswamy H S, "Symbolic representation of two-dimensional shapes", Pattern Recognition Letters 28 (2007) 144-155 (2007).
[24]Prakash H N and Guru D S, "online signature verification and Recognition: An Approach based on symbolic Representation", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 31, No 6, June (2009).
[25]Mohan Kumar H P and Nagendraswamy H S, "Gait Recognition Based on Symbolic Representation," International Journal of Machine Intelligence, Vol. 3, Issue 4, December 2011, pp-295-301 (2011).
[26]Mohan Kumar H P and Nagendraswamy H S, "Gait Recognition: An Approach based on Interval Valued Features", 978-1-4673-2906-4/13 IEEE.
[27]Carsten Hoilund, "The Radon Transform", Aalborg University, VGIS, 07gr721, November 12, 2007.
[28]P.J.Philips, H. Moon, S Rizvi, and P.Rauss, " The FERET Evaluation Methodology for Face-Recognition Algorithms," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22 No 10, pp. 1090-1104, Oct 2000.
[29]Yan-qiu Liu and Xu Wang, "Human gait recognition for Multiple views", Elsevier Procedia Engineering 15 (2011) 1832-1836.
[30]Su-li XU and Qian-jin Zhang, "Gait Recognition using Fuzzy principal component Analysis ", 978-1-4244-5895-0/10 2010 IEEE.
[31]Khalid Bashir, Tao Xiang and Shaogang Gong, "Gait recognition without subject cooperation", Pattern Recognition letters 31 (2010) 2052-2060.
[32]Heesung Lee, Sungjun Hong, Imran Fareed Nizami and Euntai Kim, "A Noise Robust Gait Representation: Motion Energy Image", International Journal of control Automation, and Systems (2009) 7(4):638-643.
[33]Byungyun Lee, Sunngjun Hong, Heesung Lee, Euntai Kim, "Gait Recognition system using Decision-level Fusion", 978-1-4244-5046-6/10 2010 IEEE.