Modeling and Recognition of Arbitrary Curved Objects from Image Contours

这是为期三年的连续奖项的第一年。这项研究致力于下一代基于模型的视觉系统，它应该演示从大型模型数据库中选择的复杂曲面对象的单目图像数据的识别。这将需要在形状表示、建模和匹配领域取得重大进展。研究了一种新的形状表示方法及其在距离和视频图像自动建模和目标识别中的应用，包括方面图的构建、姿态计算和模型数据库的索引。在本研究中，任意光滑的三维形状由一组特征曲面曲线来表示，这些特征曲面曲线的性质决定了图像轮廓的结构及其灾难性变化，并且这些曲线中的一些与单目轮廓特征之间存在着自然的对应关系。

This is the first year of a three-year continuing award. The research addresses the next generation of model-based vision systems, which should demonstrate the recognition in monocular image data of complex curved objects selected from a large database of models. This will require major progress in the areas of shape representation, modeling, and matching. This research focuses on a novel shape representation and its application to automatic model construction from sets of range and video images and to object recognition, including aspect graph construction, pose computation, and indexing into a database of models. In this research, arbitrary smooth 3D shapes are represented by a set of characteristic surface curves having the properties that they determine the structure of the image contours and its catastrophic changes, and there is a natural correspondence between some of these curves and monocular contour features such as inflections and bitangents.