Tu Liyun, Yang Dan, Vicory Jared, Zhang Xiaohong, Pizer Stephen M, Styner Martin
College of Computer Science, Chongqing University, Chongqing 400044 China, and also with the Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599 USA.
College of Computer Science, Chongqing University, Chongqing 400044 China.
IEEE Signal Process Lett. 2015 Dec;22(12):2269-2273. doi: 10.1109/LSP.2015.2476366. Epub 2015 Sep 3.
We present a scheme that propagates a reference skeletal model (s-rep) into a particular case of an object, thereby propagating the initial shape-related layout of the skeleton-to-boundary vectors, called spokes. The scheme represents the surfaces of the template as well as the target objects by spherical harmonics and computes a warp between these via a thin plate spline. To form the propagated s-rep, it applies the warp to the spokes of the template s-rep and then statistically refines. This automatic approach promises to make s-rep fitting robust for complicated objects, which allows s-rep based statistics to be available to all. The improvement in fitting and statistics is significant compared with the previous methods and in statistics compared with a state-of-the-art boundary based method.
我们提出了一种方案，该方案将参考骨骼模型（s-表示）传播到对象的特定实例中，从而传播骨骼到边界向量（称为辐条）的初始形状相关布局。该方案通过球谐函数表示模板以及目标对象的表面，并通过薄板样条计算它们之间的变形。为了形成传播后的s-表示，它将变形应用于模板s-表示的辐条，然后进行统计细化。这种自动方法有望使s-表示拟合对于复杂对象具有鲁棒性，这使得基于s-表示的统计数据可供所有人使用。与以前的方法相比，拟合和统计方面的改进非常显著，与基于边界的最新方法相比，统计方面的改进也很显著。
