A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
OpenGL(R) Programming Guide: The Official Guide to Learning OpenGL(R), Version 2 (5th Edition) (OpenGL)
Seam carving for content-aware image resizing
ACM SIGGRAPH 2007 papers
Improved seam carving for video retargeting
ACM SIGGRAPH 2008 papers
Optimized scale-and-stretch for image resizing
ACM SIGGRAPH Asia 2008 papers
Fast structure-preserving image retargeting
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Optimized image resizing using seam carving and scaling
ACM SIGGRAPH Asia 2009 papers
A system for retargeting of streaming video
ACM SIGGRAPH Asia 2009 papers
Image resizing via non-homogeneous warping
Multimedia Tools and Applications
EGSR'06 Proceedings of the 17th Eurographics conference on Rendering Techniques
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Image retargeting is the process of adapting an existing image to display with arbitrary sizes and aspect ratios. A compelling retargeting method aims at preserving the viewers' experience by maintaining the significant regions in the image. In this paper, we present a novel image retargeting method based on non-uniform mesh warping, which can effectively preserve both the significant regions and the global configuration of the image. The main idea of our method is sampling mesh vertices based on the saliency map, that is to say, we place mesh vertices more densely in the significant regions, defining different quadratic error metrics to measure image distortion and adopting a patch-linking scheme that can better preserve the global visual effect of the entire image. Moreover, to increase efficiency, we formulate the image retargeting as a quadratic minimization problem carried out by solving linear systems. Our experimental results verify its effectiveness.