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Saliency for Image Manipulation
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| Abstract |
Every picture tells a story. In photography,the story is portrayed by a composition of objects, commonly referred to as the subjects of the piece. Were we to remove these objects, the story would be lost. When manipulating images, either for artistic rendering or cropping, it is crucial that the story of the piece remains intact. As a result, the knowledge of the location of these prominent objects is essential. We propose an approach for saliency detection that combines previously suggested patch distinctness with an object probability map. The object probability map infers the most probable locations of the subjects of the photograph according to highly distinct salient cues. The benefits of the proposed approach are demonstrated through state-of-the-art results on common data-sets. We further show the benefits of our method in various manipulations of real world photographs while preserving their meaning.
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| Software |
This code is based on the following papers (with some small modifications):
- R. Margolin, L. Zelnik-Manor, and A. Tal, "Saliency For Image Manipulation", To appear in The Visual Computer, 2012.
- R. Margolin, L. Zelnik-Manor, and A. Tal, "Saliency For Image Manipulation", Computer Graphics International (CGI) 2012.
Please cite this work if you use our software
Our code includes the code taken from:
- Ming-Ming Cheng, Guo-Xin Zhang, Niloy J. Mitra, Xi-aolei Huang, and Shi-Min Hu. Global contrast based salient region detection. In CVPR, pages 409-416, 2011
The code in this website is for demo purposes only.
Individuals or academic institutes are free to use the saliency maps generated using this version as long as they acknowledge its use.
Commercial licensing is managed by the Technion Industry Liaison Office. Please contact Hovav Gazit for details.
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