Shape Representation in Practice

摘要提案#0098169 Annamaria B Amenta德克萨斯大学该奖项包括两个关于从真实世界数据重建形状的项目，第一个是自动化寻找分子模型构象的过程，以匹配X射线衍射产生的电子密度图。这是蛋白质生物化学中的一个重要问题，目前通过费力的用户交互来解决。我们最近关于中轴结构的研究应该有助于建立密度图形状的简明编码，我们可以搜索与分子模型相匹配的特征。第二个项目是采用二维图像处理技术，通过结合激光测距扫描仪捕获的许多低分辨率点集来产生物体的高分辨率三维模型。这将允许自动构建真实的对象的非常高分辨率的模型，用于诸如定制医疗器械的应用。采用该技术的关键是开发扫描仪本身的计算模型，这是一种非常非传统的成像设备。

ABSTRACTProposal #0098169Annamaria B AmentaUniversity of TexasThe award comprises two projects concerning shape reconstruction from real-world data.The first is to work on automating the process of finding a conformation of a molecular model to match an electron density map produced by X-ray diffraction. This is a important problem in protein biochemistry, currently solved by laborious user interaction. Our recent research on the construction of the medial axis should be useful for building a concise encoding of the shape of the density map, which we can search for features to match to the molecular model.The second project is to adapt a two-dimensional image processing technique to produce a high-resolution three-dimensional model of an object by combining many low-resolution point sets cap-tured by a laser range scanner. This would allow the automatic construction of very high-resolution models of real objects, for applications such as customized medical appliances. The key to adapting the technology will be developing a computational model of the scanner itself, a very non-traditional imaging device.