Paper Details: Downloads: 287
Serial Number: P1150508001
Title: Apply Neural Schemes to Deformation Objects
Authors: Yu-Ju Shen and Ming-Shi Wang
Abstract: In this paper, a novel Self-organizing mapping (SOM) neural network is proposed for identifying and simulating deformation objects. The weights of the network nodes can be initialized according to the mass and spring parameters. SOM is a very simple and easy means of visualization. The proposed method support adaptive time steps, and dynamic modifications of physical parameters, including mass and spring ' s stiffness . The advantage of the proposed method is that an external force can be simply added to any node of the model and the structure of the object freely adjusted. Simulation results show that the SOM neural network presents a convincing model of deformation objects and provide an alternative approach of solving this class of physics-based models.
Keywords: Virtual Reality, Self-organizing maps, Neural Network, Visualization.
Journal/Conference: International Journal of Graphics, Vision and Image Processing
Volume:
Issue:
Submission Date: 1/1/2005 12:00:00 AM
Review Date: 2/1/2005 12:00:00 AM
Publishing Date: 4/1/2005 12:00:00 AM
Article Downloads: 287
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