Non-Parametric Shape Recovery for Computer Vision

今年是连续三年获奖的第一年。 的 研究致力于从物体的2D形状恢复其3D形状， 图像轮廓 现有的3D形状恢复算法往往依赖于 在参数化模型上唯一地约束底层3D 面 通常，真实世界的场景过于笼统，无法描述 使用参数模型。 研究人员发现， 某些非参数形状模型允许更大的灵活性 而同时提供可用于 形状恢复过程。使用平面对称作为模型， PI已经构建了一个对称分析器SYMAN，它可以找到 轮廓对称。此外，他还开发了算法， 使用对称性和正交性作为基于对象的几何学， 从图像轮廓约束或恢复3D形状。 有了这个奖， 该研究扩展到表面的数学研究， 对称曲面的射影性质及其 应用于形状恢复问题，以及使用 通过观察来描述和恢复形状的“晶体学”方法 具有相似结构的形状类是等价的，因此 所有"八进制对称"对象（例如，球体，立方体， 超二次曲面）可以被认为是等价的。

This is the first year of a three-year continuing award. The research addresses recovering the 3D shape of an object from its 2D image contour. Existing 3D shape recovery algorithms tend to rely on parametric models to uniquely constrain the underlying 3D surface. Often, real-world scenes are too general to describe using parametric models. This researcher has discovered that certain non-parametric shape models allow a much greater flexibilty while at the same time providing constraints that can be used in the shape recovery process. Using planar symmetry as a model, the PI has constructed a symmetry analyzer, SYMAN, that finds axes of symmetry from contour. In addition, he has developed algorithms that use symmetry and orthogonality as object-based heuristics to constrain or recover 3D shape from image contour. With this award, the research is extended to mathematical study of the surface and projective properties of curved symmetric surfaces as well as their application to the shape recovery problem, and use of "crystallographic" methods to describe and recover shape by viewing classes of shapes with similar structure as being equivalent, so that all "octally symmetric" objects (e.g., spheres, cubes, superquadrics) might be considered equivalent.