Abstract
Efficient multi-scale manifold reconstruction from point clouds can be obtained through the Hierarchical Radial Basis Function (HRBF) network. An online training procedure for HRBF is here presented and applied to real-time surface reconstruction during a 3D scanning session. Results show that the online version compares well with the batch one.
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References
Saad, D. (ed.): On-Line Learning in Neural Networks. Cambr. Univ. Press, Cambridge (1998)
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford Univ. Press, New York (1995)
Alexandridis, A., Sarimveis, H., Bafas, G.: A new algorithm for online structure and parameter adaptation of RBF networks. Neural Networks 16(7), 1003–1017 (2003)
Freeman, J.A.S., Saad, D.: Online learning in radial basis function networks. Neural Computation 9(7), 1601–1622 (1997)
Rubaai, A., Kotaruand, R., Kankam, M.D.: Online training of parallel neural network estimators for control of induction motors. IEEE Trans. on Ind. Appl. 37(5), 1512–1521 (2001)
Fan, J., Dimitrova, N., Philomin, V.: Online face recognition system for videos based on modified probabilistic neural networks. In: Proc. of the 2004 Int. Conf. on Image Processing, 2004. ICIP ’04, vol. 3, pp. 2019–2022 (2004)
Borghese, N.A., Ferrigno, G., Baroni, G., Ferrari, S., Savaré, R., Pedotti, A.: Autoscan: a flexible and portable 3D scanner. IEEE C. G. & A. 18(3), 38–41 (1998)
Rusinkiewicz, S., Hall-Holt, O., Levoy, M.: Real-time 3D model acquisition. In: Proc. of the 29th conf. on Comp. graph. and int. tech., pp. 438–446. ACM Press, New York (2002)
Rusinkiewicz, S., Levoy, M.: Qsplat: A multiresolution point rendering system for large meshes. In: Proc. of SIGGRAPH 2000, pp. 343–352 (2000), (ISBN 1-58113-208-5)
Ferrari, S., Frosio, I., Piuri, V., Borghese, N.A.: Automatic multiscale meshing through HRBF networks. IEEE Trans. on I. & M. 54(4), 1463–1470 (2005)
Girosi, F., Jones, M., Poggio, T.: Regularization theory and neural networks architectures. Neural Computation 7(2), 219–269 (1995)
Platt, J.: A resource-allocating network for function interpolation. Neural Computation 3(2), 213–225 (1991)
Fritzke, B.: Growing cell structures — A self-organizing network for unsupervised and supervised learning. Neural Networks 7(9), 1441–1460 (1994)
Ferrari, S., Borghese, N.A., Piuri, V.: Multiscale models for data processing: an experimental sensitivity analysis. IEEE Trans. on I. & M. 50(4), 995–1002 (2001)
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Bellocchio, F., Ferrari, S., Piuri, V., Borghese, N.A. (2007). Online Training of Hierarchical RBF. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_8
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DOI: https://doi.org/10.1007/978-3-540-74819-9_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
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