Abstract
This paper investigates that loose clothing such as wearing dresses and human body shapes create individual eigenspaces and, as a result, conventional appearance-based method cannot be effective for recognizing human body postures. We introduce a dress effect due to loose clothing and a figure effect due to various human body shapes in this particular study. This study particularly proposes an image pre-processing by ‘Laplacian of Gaussian (LoG) ’ filter over input images and a ‘mean posture matrix ’ for creating an eigenspace in order to overcome the preceding effects. We have tested the proposed approach on various dress environments and body shapes, and robustness of the method has been demonstrated.
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References
Sirovich, L., Kirby, M.: Low dimensional procedure for the characterization of human faces. J. Optical Society of America 4(3), 519–524 (1987)
Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces, Proc. of the Computer Vision and Pattern recognition, pp. 586–591 (1991)
Leonardis, A., Bischof, H.: Robust recognition using eigenimages. Computer Vision and Image Understanding 78, 99–118 (2000)
Ohba, K., Ikeuchi, K.: Detectability, uniqueness, and reliability of eigen windows for stable verification of partially occluded objects. IEEE Tran. on Pattern Analysis and Machine Intelligence, PAMI-9, 1043–1047 (1997)
Borotschnig, H., et al.: Appearance-based active object recognition. Image and Vision Computing 18(9), 715–727 (2000)
Black, M.J., Jepson, A.D.: Eigen tracking: robust matching and tracking of articulated objects using view-based representation. Int. Journal of Computer Vision 26(1), 63–84 (1998)
Murase, H., Nayar, S.K.: Visual learning and recognition of 3-D objects from appearance. Int. J. Computer Vision 14(5), 39–50 (1995)
Tenenbaum, B., Freeman, W.T.: Separating style and content with bilinear models. Neural Computation 12(6), 1247–1283 (2000)
Beymer, D., Poggio, T.: Face Recognition from one example view. In: Proc. of Int. Conf. on Computer Vision, pp. 500–507 (1995)
Moghaddam, B., et al.: Bayesian face recognition. Pattern Recognition 33, 1771–1782 (2000)
Romer, R., Stan, S.: Specialized mapping and the estimation of human body pose from a single image. In: IEEE Workshop on Human Motion (2002)
Murase, R.S.: Moving object recognition in eigenspace representation: Gait Analysis and lip reading. Pattern Recognition Letters 17, 155–162 (1996)
Yilmaz, A., Gokmen, M.: Eigenhill vs. eigenface and eigenedge. Pattern Recognition 34, 181–184 (2001)
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© 2004 Springer-Verlag Berlin Heidelberg
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Rahman, M.M., Ishikawa, S. (2004). Applying Image Pre-processing Techniques for Appearance-Based Human Posture Recognition: An Experimental Analysis. In: Webb, G.I., Yu, X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science(), vol 3339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30549-1_14
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DOI: https://doi.org/10.1007/978-3-540-30549-1_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24059-4
Online ISBN: 978-3-540-30549-1
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