Research Article | OPEN ACCESS
Optimized Real Time Vertex Based Deformation Using Octree and Two Neighborhood Method
Irshad Ahmad, Suziah Bt. Sulaiman and Dayang Rohaya Bt Awang Rambli
Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak, Malaysia
Research Journal of Applied Sciences, Engineering and Technology 2013 17:4240-4245
Received: June 28, 2012 | Accepted: August 08, 2012 | Published: May 01, 2013
Abstract
Soft tissue simulation is very important in medical simulation and learning procedures. But such simulations require intensive computation. With the force feedback devices, the computation required should be much faster as touch sensation is approximately 20 times faster than that of visual. Efficient collision detection techniques are required to quickly locate the touched node of the model and a few triangles of the model need to be rendered in the haptic loop to get further optimization while achieving the same haptic sensation. In this study an octree space partitioning method is used for collision detection to find the touched node quickly and two circular rings of neighbors of the touched node are rendered in the haptic loop for further optimization. This technique is implemented in our previously developed real time vertex based deformation. The results are compared with the previous method which shows better performance.
Keywords:
Deformation, interactive, modified slope intercept form, Octree Space Partitioning,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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