A content-aware image resizing method with prominent object size adjusted

  • Authors:
  • Meiling Shi;Lei Yang;Guoqin Peng;Dan Xu

  • Affiliations:
  • Yunnan University;Yunnan University;Yunnan University;Yunnan University

  • Venue:
  • Proceedings of the 17th ACM Symposium on Virtual Reality Software and Technology
  • Year:
  • 2010

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Abstract

A novel method that prominent object size can be controlled during image resizing is proposed in this paper. By a simple parameter adjustment, this new method can change the primary object size according to user preference. To accomplish this, we present a new quad distortion energy criterion by considering both the shape and the size of a quad. Moreover, we improve the single resolution visual attention model based on the rarity of features to a multiresolution saliency model. Then, redefine the significance map as the weighted average of this multi-resolution saliency result and gradient magnitude.