Abstract
Automatic object positioning in 3D space is nowadays required by a great variety of applications. We propose here a new approach to this problem, whose core is constituted by a bank of neural networks; from the measured positions of a set of laser spots generated on the object surface, the nets estimate the position of a set of points rigidly connected to the object. Results on synthetic data are reported, and show that the proposed method is reliable and comparable in accuracy with the most common solutions present in the literature, which are based on Iterative Closest Point (ICP) matching.
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References
Baroni, G., Troia, A., Riboldi, M., Orecchia, R., Ferrigno, G., Pedotti, A. (2003) Evaluation of methods for opto-electronic body surface sensing applied to patient position control in breast radiation therapy. Med. Biol. Eng. Comput., 41, pp. 679–688.
Besl, P. J., McKay, N. D. (1992) A method for registration of 3-d shapes. IEEE Trans. Pattern Analysis and Machine Intelligence, 14, pp. 239–256.
Borghese N.A., Ferrigno G., Baroni G., Savarè R., Ferrari S. and Pedotti A. (1998) AUTOSCAN: A flexible and portable scanner of 3D surfaces. IEEE Computer Graphics & Applications, pp. 38–41.
De Momi E., Frosio I., Baroni G. and Ferrigno G. (2003) FNNVM, a new fast neurocomputational approach to surfaces alignment in image guided knee replacement. Procedings of CAOS 2003, Marbella, Spain.
Hagan, M. T., Menhaj, M. (1994) Training feedforward networks with the Marquardt algorithm. IEEE Trans. Neural Networks, 5, pp. 989–993.
Hager, G. D. (1997) A modular system for robust positioning using feedback from stereo vision. IEEE Trans. On Robotics and Automation, 13, pp. 582–595.
Wang, L. A., Solberg, T. D., Medin P. M. and Boone R. (2001) Infrared patient positioning for stereotactic radiosurgery of extracranial tumors. Computer in Biology and Medicine, 31, pp. 101–111.
Yang, M. H., Kriegman, D. J., Ahuja, N. (2002) Detecting faces in images: a survey. IEEE Trans. on Pattern Analysis and Machine Intell., 24, pp. 34–58.
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Frosio, I., Ferrigno, G., Borghese, N.A. (2005). A Neural Algorithm for Object Positioning in 3D Space Using Optoelectronic System. In: Apolloni, B., Marinaro, M., Tagliaferri, R. (eds) Biological and Artificial Intelligence Environments. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3432-6_38
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DOI: https://doi.org/10.1007/1-4020-3432-6_38
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-3431-2
Online ISBN: 978-1-4020-3432-9
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