中文摘要：

图象 compositing 广泛地被用来从分开的来源图象把视觉元素合为一幅单个图象。尽管最近的图象 compositing 技术能够完成从不同来源的视觉元素的光滑的相配，他们中的大多数含蓄地假设来源图象在一样的观点被拿。在这份报纸，我们在场从多重来源的 compositing 小说图象目标的一条途径想象哪个有不同观点。我们的关键想法是为来源图象目标的有意义的部件构造 3D 代理，并且使用这些 3D 部件代理在一样的观点一起弄歪并且无缝地合并部件。认识到这个想法，我们介绍一个并列框架的基于的单个看法的照相机刻度算法处理图象对象的一般类型，得到长方体的一个结构知道的长方体优化算法正确结构关系地为图象对象部件代理，并且最后， 3D 代理转变指导了图象变弯缝对象部件的算法。我们进一步基于这条 compositing 途径描述一个新奇应用程序自动地综合从一套模范的很多图象对象。试验性的结果证明我们的 compositing 途径能被用于许多图象目标，例如椅子，杯，灯，和机器人，并且合成申请能从模范的一个小集合与重要形状和风格变化创造新奇图象目标。

英文摘要：

Image compositing is widely used to combine visual elements from separate source images into a single image. Although recent image compositing techniques are capable of achieving smooth blending of the visual elements from different sources, most of them implicitly assume the source images are taken in the same viewpoint. In this paper, we present an approach to compositing novel image objects from multiple source images which have different viewpoints. Our key idea is to construct 3D proxies for meaningful components of the source image objects, and use these 3D component proxies to warp and seamlessly merge components together in the same viewpoint. To realize this idea, we introduce a coordinate- frame based single-view camera calibration algorithm to handle general types of image objects, a structure-aware cuboid optimization algorithm to get the cuboid proxies for image object components with correct structure relationship, and finally a 3D-proxy transformation guided image warping algorithm to stitch object components. We further describe a novel application based on this compositing approach to automatically synthesize a large number of image objects from a set of exemplars. Experimental results show that our compositing approach can be applied to a variety of image objects, such as chairs, cups, lamps, and robots, and the synthesis application can create novel image objects with significant shape and style variations from a small set of exemplars.