Abstract
Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications. We propose a new approach to extract human joints (vertex positions) using a model-based method. Motion templates describing the motion of the joints as derived by gait analysis, are parametrized using the elliptic Fourier descriptors. The heel strike data is exploited to reduce the dimensionality of the parametric models. People walk normal to the viewing plane, as major gait information is available in a sagittal view. The ankle, knee and hip joints are successfully extracted with high accuracy for indoor and outdoor data. In this way, we have established a baseline analysis which can be deployed in recognition, marker-less analysis and other areas. The experimental results confirmed the robustness of the proposed method to recognize walking subjects with a correct classification rate of %92.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Wang, L.A., Hu, W.M., Tan, T.N.: Recent developments in human motion analysis. Pattern Recognition 36(3), 585–601 (2003)
Aggarwal, J.K., et al.: Nonrigid motion analysis: Articulated and elastic motion. CVIU 70(2), 142–156 (1998)
Yoo, J.H., Nixon, M.S., Harris, C.J.: Extraction and description of moving human body by periodic motion analysis. In: Proc. ISCA 17th International Conference on Computers and Their Applications, pp. 110–113 (2002)
Akita, K.: Image sequence analysis of real world human motion. Pattern Recognition 17(1), 73–83 (1984)
Guo, Y., Xu, G., Tsuji, S.: Understanding human motion patterns. In: Proc. the 12th IAPR International Conference on Pattern Recognition, vol. 2, pp. 325–329 (1994)
Rohr, K.: Towards model-based recognition of human movements in image sequences. CVGIP: IU 74(1), 94–115 (1994)
Karaulova, I.A., Hall, P.M., Marshall, A.D.: A hierarchical model of dynamics for tracking people with a single video camera. In: Proc. of the 11th BMVC, Sept. 2000, pp. 262–352 (2000)
Huazhong, N., et al.: People tracking based on motion model and motion constraints with automatic initialization. Pattern Recognition 37(7), 1423–1440 (2004)
Shio, A., Sklansky, J.: Segmentation of people in motion. In: IEEE Workshop on Visual Motion, vol. 2, Octobor 1991, pp. 325–332. IEEE Computer Society Press, Los Alamitos (1991)
Kurakake, S., Nevatia, R.: Description and tracking of moving articulated objects. In: Proc. 11th IAPR ICPR, Oct. 1992, vol. 1, pp. 491–495 (1992)
Cunado, D., Nixon, M.S., Carter, J.N.: Automatic Extraction and Description of Human Gait Models for Recognition Purposes. Computer Vision and Image Understanding 90(1), 1–41 (2003)
Grant, M.G., Nixon, M.S., Lewis, P.H.: Extracting moving shapes by evidence gathering. Pattern Recognition 35(5), 1099–1114 (2002)
Granlund, G.H.: Fourier preprocessing for hand print character recognition. IEEE T-Comp 21, 195–201 (1972)
Aguado, A.S., Nixon, M.S., Montiel, M.E.: Parameterising arbitrary shapes via fourier descriptors for evidence-gathering extraction. CVGIP: IU 2, 547–551 (1998)
Leavers, V.F.: Which Hough transform?. CVGIP: Image Understanding 58(2), 250–264 (1993)
Aguado, A.S., Nixon, M.S., Montiel, M.E.: Parameterizing Arbitrary Shapes via Fourier Descriptors for Evidence-Gathering Extraction. CVIU 69(2), 202–221 (1998)
Cutler, R., Davis, L.S.: Robust real-time periodic motion detection, analysis, and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(8), 781–796 (2003)
Bouchrika, I., Nixon, M.S.: People Detection and Recognition using Gait for Automated Visual Surveillance. In: IEE International Symposium on Imaging for Crime Detection and Prevention (2006)
Fujiyoshi, H., Lipton, A.J., Kanade, T.: Real-time human motion analysis by image skeletonization. IEICE Trans. on Information and System, 113–120 (2004)
Pheasant, S.T.: Body space: Anthropometry, Ergonomics and Design. Taylor & Francis, Abington (1988)
Shutler, J.D., et al.: On a large sequence-based human gait database. In: Proceedings of Recent Advances in Soft Computing, Nottingham, UK, pp. 66–71 (2002)
Winter, D.A.: The Biomechanics and Motor Control of Human Movement, 2nd edn. Wiley, Chichester (1990)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Bouchrika, I., Nixon, M.S. (2007). Model-Based Feature Extraction for Gait Analysis and Recognition. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71457-6_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-71457-6_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71456-9
Online ISBN: 978-3-540-71457-6
eBook Packages: Computer ScienceComputer Science (R0)