基于改进粒子群算法的动态3D实时建模技术
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摘要
针对传统3D建模技术无法满足在脱离专业测量工具的情况下,实时创建出与用户所处房间等比例尺寸的3D模型的需求。提出一种基于陀螺仪传感器结合改进粒子群算法计算房间3D模型尺寸与镜头位置的动态3D建模技术,该技术可以实现实时房间等比例建模,使用者可以预览到整个房间所有方位的装修效果,让用户对房间整体装修效果有直观的印象,操作方便且实时性强。实验结果表明,改进粒子群算法的动态3D实时建模技术解决了国内传统3D建模技术测量不精确的缺陷,具有一定的理论和实际意义。
For the traditional 3 D modeling technology, it cannot meet the demand of 3 D models with the user's room and other dimensions in real time without the professional measurement tools. In this paper, it proposes a dynamic 3 D modeling method based on the gyroscope sensor and improved particle swarm algorithm. This method is employed to calculate the size and position of the 3 D model of the room, which can achieve real-time room scale modeling, etc., so that users can preview the decoration effect of the entire room in all directions, the overall impression of the room as a whole, easy to operate and real-time. Experimental results show that the prefabricated effect previewing system based on the improved particle swarm optimization algorithm solves the defects of inaccurate measurement in the traditional 3 D modeling techniques in China and has certain theoretical and practical significance.
For the traditional 3 D modeling technology, it cannot meet the demand of 3 D models with the user's room and other dimensions in real time without the professional measurement tools. In this paper, it proposes a dynamic 3 D modeling method based on the gyroscope sensor and improved particle swarm algorithm. This method is employed to calculate the size and position of the 3 D model of the room, which can achieve real-time room scale modeling, etc., so that users can preview the decoration effect of the entire room in all directions, the overall impression of the room as a whole, easy to operate and real-time. Experimental results show that the prefabricated effect previewing system based on the improved particle swarm optimization algorithm solves the defects of inaccurate measurement in the traditional 3 D modeling techniques in China and has certain theoretical and practical significance.
引文
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[3] Jabbar S,Naseer K,Gohar M,et al.Trust model at servicelayer of cloud computing for educational institutes[J].The Journal of Supercomputing,2016,1:58-83.
[4] Zhu Zhe,Martin R R,Pepperell R,et al.3D modelingand motion parallax for improved videoconferencing[J].Computational Visual Media,2016,7:131-142.
[5] Teng C H,Chuo K Y,Hsieh C Y.Reconstructing three-dimensional models of objects using a Kinect sensor[J].The Visual Computer,2017,9:1-17.
[6] Reem S,Abu-Rustum M,Ziade F.The 3-sweep approach:a standardized technique for fetal anatomic assessmentin the limited resource setting[J].Journal of Fetal Medicine,2017,3:25-30.
[7]张魏,雷雪,邢锋,等.基于NURBS的反射面天线曲面建模及仿真验证[J].信息工程大学学报,2017(1):31-34.
[8] Chiozzi A,Milani G,Tralli A.A genetic algorithm NURBS-based new approach for fast kinematic limit analysis ofmasonry vaults[J].Computers&Structures,2017,182:187-204.
[9] Zhang X.Research on NURBS curve interpolation algo-rithm based on filtering[J].China Mechanical Engineering,2009,20(14):1695-1699.
[10]易志福.高速高精度NURBS插补算法研究及其插补器实现[D].合肥:合肥工业大学,2017.
[11]徐阳,刘强.考虑流线场约束的NURBS曲线拟合方法[J].计算机辅助设计与图形学学报,2017(1):137-144.
[12] Hosseini-Pishrobat M,Keighobadi J.Force-balancing modelpredictive control of MEMS vibratory gyroscope sensor[J].Proceedings of the Institution of Mechanical EngineersPart C Journal of Mechanical Engineering Science,2016,230(17).
[13]周华,杨帆,吴耀宇.无人机转角偏移优化测量方法研究与仿真[J].计算机仿真,2016(4):140-143.
[14]邓科.惯性稳定平台的建模分析与高精度控制[D].合肥:中国科学技术大学,2016.
[15] Clerc M,Kennedy J.The particle swarm-explosion,sta-bility,and convergence in a multidimensional complexspace[J].IEEE Transactions on Evolutionary Computation,2002,6(1):58-73.
[16] Guedria N B.Improved accelerated PSO algorithm formechanical engineering optimization problems[J].AppliedSoft Computing,2016,40(40):455-467.
[17]唐祎玲,江顺亮,叶发茂,等.最优粒子增强探索粒子群算法[J].计算机工程与应用,2017,53(4):25-32.
[18]张楠,南敬昌,高明明.基于分组混沌PSO算法的模糊神经网络建模研究[J].计算机工程与应用,2017,53(9):31-37.
[19] Karaboga D,Basturk B.A powerful and efficient algo-rithm for numerical function optimization:Artificial BeeColony(ABC)algorithm[J].Journal of Global Optimiza-tion,2007,39(3):459-471.