In this paper an efficient method for image retargeting is pro- posed. It relies onto a mechanical model based on springs network. Each pixel displacement (compression or expan- sion) is given by the network response, according to the springs stiffness. The properties of the springs are deter- mined as function of the visual relevance of the pixels. Such model does not require any optimization, since its so- lution is obtained simply from a linear system of equations, allowing real-time application even for large images. The approach is fully automatic, though can be improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results prove that the presented method achieves results comparable or superior to reference methods, while improv- ing efficiency.
Gallea, R., Ardizzone, E., Pirrone, R. (2011). Springs-based Simulation for Image Retargeting. In Proc. of the 18h International Conference on Image Processing (ICIP 2011) (pp.1181-1184). IEEE Signal Processing Society [10.1109/ICIP.2011.6115641].
Springs-based Simulation for Image Retargeting
GALLEA, Roberto;ARDIZZONE, Edoardo;PIRRONE, Roberto
2011-01-01
Abstract
In this paper an efficient method for image retargeting is pro- posed. It relies onto a mechanical model based on springs network. Each pixel displacement (compression or expan- sion) is given by the network response, according to the springs stiffness. The properties of the springs are deter- mined as function of the visual relevance of the pixels. Such model does not require any optimization, since its so- lution is obtained simply from a linear system of equations, allowing real-time application even for large images. The approach is fully automatic, though can be improved by interactively providing cues such as geometric constraints and/or manual relevant object labeling. The results prove that the presented method achieves results comparable or superior to reference methods, while improv- ing efficiency.File | Dimensione | Formato | |
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