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陈光明, 李桂清, 刘培, 叶天阳, 冼楚华. 家居布局的层次化约束及其粒子群优化[J]. 计算机辅助设计与图形学学报, 2014, 26(10): 1603-1612.
引用本文: 陈光明, 李桂清, 刘培, 叶天阳, 冼楚华. 家居布局的层次化约束及其粒子群优化[J]. 计算机辅助设计与图形学学报, 2014, 26(10): 1603-1612.
Chen Guangming, Li Guiqing, Liu Pei, Ye Tianyang, Xian Chuhua. Hierarchical Constraints with Particle Swarm Optimization for Furniture Arrangement[J]. Journal of Computer-Aided Design & Computer Graphics, 2014, 26(10): 1603-1612.
Citation: Chen Guangming, Li Guiqing, Liu Pei, Ye Tianyang, Xian Chuhua. Hierarchical Constraints with Particle Swarm Optimization for Furniture Arrangement[J]. Journal of Computer-Aided Design & Computer Graphics, 2014, 26(10): 1603-1612.

家居布局的层次化约束及其粒子群优化

Hierarchical Constraints with Particle Swarm Optimization for Furniture Arrangement

  • 摘要: 家居布局作为虚拟场景设计的重要内容,在虚拟现实、三维游戏以及室内家居设计中都有应用.针对现有的家居自动布局方法存在约束冲突容易导致局部最优,以及由于全局优化方法收敛速度慢而达不到实时要求的问题,提出层次优化的思想化解约束冲突并采用粒子群优化算法解决布局优化问题.首先引入层次树对家具之间的约束关系进行结构化组织,避免约束冲突;然后引入粒子群优化算法进行优化求解,由于粒子群优化算法有着良好的并行结构,便于GPU加速,从而提高算法效率.通过多样化的实例对算法的有效性进行了验证,并对运行效率进行细致分析,结果表明,文中方法提升了家居布局的质量和效率.

     

    Abstract: Furniture arrangement is an important part of virtual scene design, which can be widely applied to virtual reality, 3D games and interior design.Noticing that existing methods for placing furniture are prone to converge to local optimal solutions because of constraint confliction among cost terms, we present a hierarchical optimization strategy and adopt particle swarm optimization (PSO) to solve the problem.We first introduce a hierarchical tree to structurally organize the furniture in a scene so as to avoid constraint confliction as far as possible, and then employ PSO to realize the optimization.Considering the inherently parallelizable feature of PSO, we accelerate the PSO's solving based on GPU.Experimental results show that our method can improve the quality and efficiency of furniture arrangement.

     

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