Web-image driven best views of 3D shapes

  • Authors:

  • Hong Liu;Lei Zhang;Hua Huang

  • Affiliations:

  • Xi’an Jiaotong University, School of Electronic and Information Engineering, Xi’an, China;Xi’an Jiaotong University, School of Electronic and Information Engineering, Xi’an, China;Xi’an Jiaotong University, School of Electronic and Information Engineering, Xi’an, China

  • Venue:
  • The Visual Computer: International Journal of Computer Graphics
  • Year:
  • 2012

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Abstract

The rapid advance of the Internet provides available huge database of web images. In this paper, we introduce a novel approach for automatically computing the best views of 3D shapes based on their web images. Best view selection is generally an intuitive task of getting the most information of a 3D shape. The novelty of our approach is to directly explore human perception on observing 3D shapes from the relevant web images. Those images are captured from biased views of different people, thus sufficiently reflecting view choice when observing the 3D shapes. By collecting web images possibly captured from the similar views, the best view is selected as the one possessing the most web images. We experiment our method with the shapes in Princeton Shape Benchmark (PSB), as well make comparisons with traditional geometric descriptor based approaches. The results demonstrate that our method is not only robust but also able to produce more canonical views in accordance with human perception.