Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
Contextual Priming for Object Detection
International Journal of Computer Vision
Improved seam carving for video retargeting
ACM SIGGRAPH 2008 papers
Optimized scale-and-stretch for image resizing
ACM SIGGRAPH Asia 2008 papers
Depicting procedural caustics in single images
ACM SIGGRAPH Asia 2008 papers
SIFT Flow: Dense Correspondence across Different Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Multi-operator media retargeting
ACM SIGGRAPH 2009 papers
PatchMatch: a randomized correspondence algorithm for structural image editing
ACM SIGGRAPH 2009 papers
A system for retargeting of streaming video
ACM SIGGRAPH Asia 2009 papers
ACM SIGGRAPH ASIA 2009 Courses
Motion-based video retargeting with optimized crop-and-warp
ACM SIGGRAPH 2010 papers
What we see is most likely to be what matters: visual attention and applications
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Resizing by symmetry-summarization
ACM SIGGRAPH Asia 2010 papers
A comparative study of image retargeting
ACM SIGGRAPH Asia 2010 papers
Importance filtering for image retargeting
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
IEEE Transactions on Circuits and Systems for Video Technology
How to measure the relevance of a retargeting approach?
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
Image retargeting assessment based on salient region similarity
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Technical Section: Aesthetic photo composition by optimal crop-and-warp
Computers and Graphics
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Assessing media retargeting results is not a trivial issue. When resizing one image to a particular percentage of its original size, some content has to be removed, which may affect the image's original meaning and/or composition. We examine the impact of the retargeting process on human fixations, by gathering eye-tracking data for a representative benchmark of retargeted images. We compute their derived saliency maps as input to a set of computational image distance metrics. When analyzing the fixations, we found that even strong artifacts may go unnoticed for areas outside the original regions of interest. We also note that the most important alterations in semantics are due to content removal. Since using an eye tracker is not always a feasible option, we additionally show how an existing model of prediction of human fixations also works sufficiently well in a retargeting context.