Abstract
In this paper, we propose a method to find feature in human object that used SURF algorithm, and use this information into 3D coordinate that use coordinate system transformation. In our method, first we use thinning algorithm to obtained skeleton of object, and find the endpoints in skeleton. In the second step, we try to use those endpoints to cluster skeleton, and the part number of cluster is six. Then, to cluster human object that use cluster skeleton result. Third, we use SURF algorithm to find the feature in each part in the cluster object image. In this step, we also use SAD method to ensure are correct of feature points that after SURF algorithm treatment. Finally we use the coordinate system transformation method. In this step, we use image coordinate system into world coordinate system, and show those result in our experiments result.
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References
Venkatesh, A., Cokkinides, G., Sakis Meliopoulos, A.P.: 3D-Visualization of Power System Data Using Triangulation and Subdivision Techniques. In: Proceedings of the 42nd Hawaii International Conference on System Sciences, pp. 1–8 (2009)
Bay, H., Tuytelarrs, T., Gool, L.J.V.: SURF: Speeded Up Robust Features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Bay, H., Ess, A., Tuytelarrs, T., Gool, L.J.V.: Speeded-Up Robust Features(SURF). In: Computer Vision and Image Understanding, vol. 110, pp. 346–359 (2008)
Matsuyama, T., Wu, X., Takai, T., Nobuhara, S.: Real-time 3D shape reconstruction, dynamic 3D mesh deformation, and high fidelity visualization for 3D video. In: Computer Vision and Image Understanding, vol. 96(3), pp. 393–434 (2004)
Zhang, T.Y., Suen, C.Y.: A fast parallel algorithm for thinning digital patterns. Communications of the ACM 27(3), 236–239 (1984)
Fazli, S., Pour, H.M., Bouzari, H.: Particle Filter based Object Tracking with Sift and Color Feature. In: International Conference on Machine Vision, pp. 89–93 (2009)
Vassiliadis, S., Hakkennes, E.A., Wong, J.S.S.M., Pechanek, G.G.: The Sum-Absolute- Difference Motion Estimation Accelerator. In: 24 th. EUROMICRO Conference, vol. 2, pp. 559–566 (1998)
Zhao, W.-L., Ngo, C.-W.: Scale-Rotation Invariant Pattern Entropy for Keypoint-Based Near-Duplicate Detection. Image Processing of IEEE Transactions 18(2), 412–423 (2009)
Lu, Y., Wang, L., Hartley, R., Li, H., Shen, C.: Multi-view Human Motion Capture with an Improved Deformation Skin Model. In: Computing: Techniques and Applications (DICTA) Digital Image, pp. 420–427 (2008)
Zhang, Z.: Flexible Camera Calibration By Viewing a Plane From Unknown Orientations. In: International Conference on Computer Vision, pp. 666–673 (1999)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(11), 1330–1334 (2000)
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Chang, SM., Tsai, J., Shih, T.K., Hsu, HH. (2011). A Coordinate Transformation System Based on the Human Feature Information. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_48
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DOI: https://doi.org/10.1007/978-3-642-17832-0_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17831-3
Online ISBN: 978-3-642-17832-0
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