Topology optimization is a powerful design approach that is used to determine the optimal topology in order to obtain the desired functional performance. It has been widely used to improve structural performance in en...Topology optimization is a powerful design approach that is used to determine the optimal topology in order to obtain the desired functional performance. It has been widely used to improve structural performance in engineering fields such as in the aerospace and automobile industries. However, some gaps still exist between topology optimization and engineering application, which significantly hinder the applica- tion of topology optimization. One of these gaps is how to interpret topology results, especially those obtained using the density framework, into parametric computer-aided design （CAD） models that are ready for subsequent shape optimization and manufacturing. In this paper, a new method for interpreting topology optimization results into stereolithography （STL） models and parametric CAD models is pro- posed. First, we extract the skeleton of the topology optimization result in order to ensure shape preser- vation and use a filtering method to ensure characteristics preservation. After this process, the distribution of the nodes in the boundary of the topology optimization result is denser, which will benefit the subsequent curve fitting. Using the curvature and the derivative of curvature of the uniform B-spline curve, an adaptive B-spline fitting method is proposed in order to obtain a parametric CAD model with the fewest control points meeting the requirement of the fitting error. A case study is presented to pro- vide a detailed description of the proposed method, and two more examples are shown to demonstrate the validity and versatility of the proposed method.展开更多
提出了一种基于分割区域间协同优化的立体匹配算法.该算法以图像区域为匹配基元,利用区域的彩色特征以及相邻区域间应满足的平滑和遮挡关系定义了区域的匹配能量函数,并引入区域之间的合作竞争机制,通过协同优化使所定义的匹配能量极小...提出了一种基于分割区域间协同优化的立体匹配算法.该算法以图像区域为匹配基元,利用区域的彩色特征以及相邻区域间应满足的平滑和遮挡关系定义了区域的匹配能量函数,并引入区域之间的合作竞争机制,通过协同优化使所定义的匹配能量极小化,从而得到比较理想的视差结果.算法首先对参考图像进行分割,利用相关法得到各分割区域的初始匹配;然后用平面模型对各区域的视差进行拟合,得到各区域的视差平面参数;最后,基于协同优化的思想,采用局部优化的方法对各区域的视差平面参数进行迭代优化,直至得到比较合理的视差图为止.采用Middlebury test set进行的实验结果表明,该方法在性能上可以和目前最好的立体匹配算法相媲美,得到的视差结果接近于真实视差.展开更多
文摘Topology optimization is a powerful design approach that is used to determine the optimal topology in order to obtain the desired functional performance. It has been widely used to improve structural performance in engineering fields such as in the aerospace and automobile industries. However, some gaps still exist between topology optimization and engineering application, which significantly hinder the applica- tion of topology optimization. One of these gaps is how to interpret topology results, especially those obtained using the density framework, into parametric computer-aided design （CAD） models that are ready for subsequent shape optimization and manufacturing. In this paper, a new method for interpreting topology optimization results into stereolithography （STL） models and parametric CAD models is pro- posed. First, we extract the skeleton of the topology optimization result in order to ensure shape preser- vation and use a filtering method to ensure characteristics preservation. After this process, the distribution of the nodes in the boundary of the topology optimization result is denser, which will benefit the subsequent curve fitting. Using the curvature and the derivative of curvature of the uniform B-spline curve, an adaptive B-spline fitting method is proposed in order to obtain a parametric CAD model with the fewest control points meeting the requirement of the fitting error. A case study is presented to pro- vide a detailed description of the proposed method, and two more examples are shown to demonstrate the validity and versatility of the proposed method.
文摘提出了一种基于分割区域间协同优化的立体匹配算法.该算法以图像区域为匹配基元,利用区域的彩色特征以及相邻区域间应满足的平滑和遮挡关系定义了区域的匹配能量函数,并引入区域之间的合作竞争机制,通过协同优化使所定义的匹配能量极小化,从而得到比较理想的视差结果.算法首先对参考图像进行分割,利用相关法得到各分割区域的初始匹配;然后用平面模型对各区域的视差进行拟合,得到各区域的视差平面参数;最后,基于协同优化的思想,采用局部优化的方法对各区域的视差平面参数进行迭代优化,直至得到比较合理的视差图为止.采用Middlebury test set进行的实验结果表明,该方法在性能上可以和目前最好的立体匹配算法相媲美,得到的视差结果接近于真实视差.
