Self-organizing(SO) dynamic deformation for building of 3D models
| dc.contributor | 國立臺灣師範大學資訊教育研究所 | zh_tw |
| dc.contributor.author | Chen, Sei-Wang | en_US |
| dc.contributor.author | Stockman, G. C. | en_US |
| dc.contributor.author | Chang, Kuo-En | en_US |
| dc.date.accessioned | 2014-10-30T09:32:08Z | |
| dc.date.available | 2014-10-30T09:32:08Z | |
| dc.date.issued | 1996-03-01 | zh_TW |
| dc.description.abstract | Three-dimensional (3D) modeling based on an ensemble of multilayer self-organizing (SO) neural networks is described. Our objective for 3D modeling is to construct a representation of a 3D object shape from sensed surface points acquired from the object. Current modeling techniques can be classified into two categories: the static and the dynamic approaches, where the former grounded in computational geometry, and the latter rooted in the mechanics of elastic materials. In this paper, a neural-based dynamic modeling approach is presented. The method used is proved to converge and experimental results are shown which support its applicability to real problems. | en_US |
| dc.identifier | ntnulib_tp_A0904_01_023 | zh_TW |
| dc.identifier.issn | 1045-9227 | zh_TW |
| dc.identifier.uri | http://rportal.lib.ntnu.edu.tw/handle/20.500.12235/34324 | |
| dc.language | en | zh_TW |
| dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
| dc.relation | IEEE Transactions on Neural Networks, 7(2), 374-387. (SCI, EI) | en_US |
| dc.relation.uri | http://dx.doi.org/10.1109/72.485673 | zh_TW |
| dc.title | Self-organizing(SO) dynamic deformation for building of 3D models | en_US |