从一张深度图像完成3D物体形状

Jason Rock, Tanmay Gupta, J. Thorsen, JunYoung Gwak, Daeyun Shin, Derek Hoiem
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引用次数: 156

摘要

我们的目标是从物体的深度图像中恢复完整的3D模型。现有的方法依赖于用户交互或应用于有限的对象类别,例如椅子。我们的目标是完全自动地从任何类别重建3D模型。我们采用基于范例的方法:使用基于视图的匹配在3D模型数据库中检索相似的对象,并从检索到的模型中转移对称和表面。我们研究了三种情况下的三维模型的完成:新视图(数据库中的模型);新模型(数据库中同一类别的其他对象的模型);新类别(数据库中没有该类别的模型)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Completing 3D object shape from one depth image
Our goal is to recover a complete 3D model from a depth image of an object. Existing approaches rely on user interaction or apply to a limited class of objects, such as chairs. We aim to fully automatically reconstruct a 3D model from any category. We take an exemplar-based approach: retrieve similar objects in a database of 3D models using view-based matching and transfer the symmetries and surfaces from retrieved models. We investigate completion of 3D models in three cases: novel view (model in database); novel model (models for other objects of the same category in database); and novel category (no models from the category in database).
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