The Community for Technology Leaders
RSS Icon
Issue No.06 - Nov.-Dec. (2011 vol.31)
pp: 56-66
Mathias Eitz , Technical University of Berlin
Ronald Richter , Technical University of Berlin
Kristian Hildebrand , Technical University of Berlin
Tamy Boubekeur , Telecom ParisTech
Marc Alexa , Technical University of Berlin
Photosketcher is an interactive system for progressively synthesizing novel images using only sparse user sketches as input. Photosketcher works on the image content exclusively; it doesn't require keywords or other metadata associated with the images. Users sketch the rough shape of a desired image part, and Photosketcher searches a large collection of images for it. The search is based on a bag-of-features approach that uses local descriptors for translation-invariant retrieval of image parts. Composition is based on user scribbles: from the scribbles, Photosketcher predicts the desired part using Gaussian mixture models and computes an optimal seam using graph cuts. To further reduce visible seams, users can blend the composite image in the gradient domain.
image databases, image retrieval, image segmentation, image synthesis, sketching, computer graphics, graphics and multimedia
Mathias Eitz, Ronald Richter, Kristian Hildebrand, Tamy Boubekeur, Marc Alexa, "Photosketcher: Interactive Sketch-Based Image Synthesis", IEEE Computer Graphics and Applications, vol.31, no. 6, pp. 56-66, Nov.-Dec. 2011, doi:10.1109/MCG.2011.67
1. J. Hays and A.A. Efros, "Scene Completion Using Millions of Photographs," ACM Trans. Graphics, vol. 26, no. 3, 2007, article 4.
2. A. Agarwala et al., "Interactive Digital Photomontage," ACM Trans. Graphics, vol. 23, no. 3, 2004, pp. 294–302.
3. M. Eitz et al., "Sketch-Based Image Retrieval: Benchmark and Bag-of-Features Descriptors," to be published in IEEE Trans. Visualization and Graphics, 2011.
4. J. Sivic and A. Zisserman, "Video Google: A Text Retrieval Approach to Object Matching in Videos," Proc. 9th Int'l Conf. Computer Vision, IEEE CS Press, 2003, pp. 1470–1477.
5. C.M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
6. Y. Boykov and V. Kolmogorov, "An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 9, 2004, pp. 1124–1137.
7. P. Pérez, M. Gangnet, and A. Blake, "Poisson Image Editing," ACM Trans. Graphics, vol. 22, no. 3, 2003, pp. 313–318.
8. C. Rother, V. Kolmogorov, and A. Blake, "'Grab-Cut'—Interactive Foreground Extraction Using Iterated Graph Cuts," ACM Trans. Graphics, vol. 23, no. 3, 2004, pp. 309–314.
9. T. Chen et al., "Sketch2Photo: Internet Image Montage," ACM Trans. Graphics, vol. 28, no. 5, 2009, article 124.
10. J.-F. Lalonde et al., "Photo Clip Art," ACM Trans. Graphics, vol. 26, no. 3, 2007, article 3.
35 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool