›› 2016, Vol. 31 ›› Issue (3): 463-478.doi: 10.1007/s11390-016-1640-8

Special Issue: Artificial Intelligence and Pattern Recognition; Computer Graphics and Multimedia

• Special Section of CVM 2016 • Previous Articles     Next Articles

View-Aware Image Object Compositing and Synthesis from Multiple Sources

Xiang Chen1, Member, ACM, Wei-Wei Xu1, Member, IEEE, Sai-Kit Yeung2, Member, IEEE, and Kun Zhou1,*, Fellow, IEEE   

  1. 1 State Key Laboratory of Computer Aided Design and Computer Graphics, Zhejiang University Hangzhou 310058, China;
    2 Vision, Graphics and Computational Design Group, Singapore University of Technology and Design Singapore 487372, Singapore
  • Received:2015-11-28 Revised:2016-03-07 Online:2016-05-05 Published:2016-05-05
  • Contact: Kun Zhou E-mail:kunzhou@acm.org
  • Supported by:

    This work is partially supported by the National Natural Science Foundation of China under Grant Nos. 61272305, 61303136, 61272392, and 61322204, and the National Program for Special Support of Eminent Professionals of China.

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 coordinateframe 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.

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