Transferring color to greyscale images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
IEEE Computer Graphics and Applications
Shape Matching and Object Recognition Using Shape Contexts
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ACM SIGGRAPH 2004 Papers
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ACM SIGGRAPH 2004 Papers
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CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
ACM SIGGRAPH 2006 Papers
Hownet And the Computation of Meaning
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ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
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ACM SIGGRAPH 2009 papers
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Color compatibility from large datasets
ACM SIGGRAPH 2011 papers
Semantic colorization with internet images
Proceedings of the 2011 SIGGRAPH Asia Conference
Global contrast based salient region detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
EGSR'05 Proceedings of the Sixteenth Eurographics conference on Rendering Techniques
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An important role of image color is the conveyer of emotions (through color themes). The colorization is less useful with an undesired color theme, even semantically correct, which has been rarely considered previously. In this paper, we propose a complete system for the image colorization with an affective word. We only need users to assist object segmentation along with text labels and give an affective word. First, the text labels along with other object characters are jointly used to filter the internet images to give each object a set of semantically correct reference images. Second, we select a set of color themes according to the affective word based on art theories. With these themes, a generic algorithm is adopted to select the best reference for each object. Finally, we propose a hybrid texture synthesis approach to colorize each object. Our experiments show that the results of our system have both the correct semantics and the desired emotions.