通过视觉船体和豪斯多夫距离确定3D物体的特征视图

A. Theetten, Jean-Philippe Vandeborre, M. Daoudi
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引用次数: 5

摘要

如今,随着私有数据库或网络上的3D对象表示呈指数级增长,从某些角度匹配这些对象的需求越来越大。为了改进它们的匹配结果,我们对一个对象的特征视图进行了研究。本研究的目的是找出需要多少个特征视图以及什么相对位置是最优的。这就是为什么使用视觉船体的原因。从一些2D遮罩中,计算最接近原始对象的可能3D网格。OpenGL视图用于从给定集合中构建3D模型的视觉外壳,然后利用Hausdorff距离测量视觉外壳与模型之间的距离。然后推导出最佳视点参数以减小距离。这些照片表明,三个正交的视图所得到的结果非常接近于在一个等面体上12个视图所得到的结果。讨论了其他一些关于视场分辨率和视场的结果。
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Determining characteristic views of a 3D object by visual hulls and Hausdorff distance
Nowadays, with the exponential growing of 3D object representations in private databases or on the web, it is all the more required to match these objects from some views. To improve the results of their matching, we work on the characteristic views of an object. The aim of this study is to find how many characteristic views are required and what relative positions are optimal. This is the reason why the visual hulls are used. From some 2D masks, the nearest possible 3D mesh from the original object is computed. OpenGL views are used to build the visual hulls of 3D models from a given collection and then the distance between the visual hulls and the models are measured thanks to the Hausdorff distance. Then the best view parameters are deduced to reduce the distance. These shots show that three orthogonal views give results very close to the ones given by twelve views on a isocahedron. Some other results on the view resolution and the field of view are discussed.
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