A similarity measure for illustration style

ACM Transactions on Graphics

Volumn 33, Issue 4, 2014, Pages

  Garces, Elena ^a   Agarwala, Aseem ^b   Gutierrez, Diego ^a   Hertzmann, Aaron ^b  

^a UNIVERSITY OF ZARAGOZA   (Spain)

^b ADOBE RESEARCH   (United States)

Author keywords

Crowd sourcing; Illustration; Learning; Style

Indexed keywords

COMPUTER SCIENCE; COMPUTER SYSTEMS;

CLIP ART; CROWD-SOURCING; ILLUSTRATION; LEARNING; PERCEPTUAL SIMILARITY; SIMILARITY MEASURE; STYLE; CROWD SOURCING; FEATURE WEIGHTING;

INTERACTIVE COMPUTER GRAPHICS;

EID: 84905756453     PISSN: 07342071     EISSN: 15577333     Source Type: Journal    
DOI: 10.1145/2601097.2601131     Document Type: Conference Paper

References (35)

1. AUCOUTURIER, J.-J., AND PACHET, F. 2002. Music Similarity Measures: What's the Use? In Proc. SMIR, 157-163.
2. BAE, S., PARIS, S., AND DURAND, F. 2006. Two-scale tone management for photographic look. ACM Trans. Graphics 25, 3, 637-645.
3. BELL, R. M., AND KOREN, Y. 2007. Lessons from the Netflix Prize Challenge. SIGKDD Explor. Newsl. 9, 2, 75-79.
4. CHEN, T., CHENG, M.-M., TAN, P., SHAMIR, A., AND HU, S.-M. 2009. Sketch2photo: Internet image montage. ACM Trans. Graphics 28, 5, 124:1-124:10.
5. CHEN, X., BENNETT, P. N., COLLINS-THOMPSON, K., AND HORVITZ, E. 2013. Pairwise Ranking Aggregation in a Crowd-sourced Setting. In Proc. WSDM, 193-202.
6. DATTA, R., JOSHI, D., LI, J., AND WANG, J. Z. 2008. Image Retrieval: Ideas, Influences, and Trends of the New Age. ACM Computing Surveys 40, 2, 5:1-5:60.
7. DOERSCH, C., SINGH, S., GUPTA, A., SIVIC, J., AND EFROS, A. 2012. What Makes Paris Look like Paris? ACM Trans. Graphics 31, 4, 101:1-101:9.
8. DURAND, F. 2002. An Invitation to Discuss Computer Depiction. In Proc. NPAR, 111-124.
9. EPSHTEIN, B., OFEK, E., AND WEXLER, Y. 2010. Detecting Text in Natural Scenes with Stroke Width Transform. In Proc. CVPR, 2963-2970.
10. GOOCH, B., AND GOOCH, A. 2001. Non-Photorealistic Rendering. AK Peters Ltd.
11. HARALICK, R. M., SHANMUGAM, K., AND DINSTEIN, I. 1973. Textural Features for Image Classification. IEEE Trans. Systems, Man and Cybernetics 3, 6, 610-621.
12. HASLER, D., AND SUSSTRUNK, S. 2003. Measuring Colour-fulness in Natural Images. In Proc. SPIE: Human Vision and Electronic Imaging, vol. 5007, 87-95.
13. HERTZMANN, A., JACOBS, C. E., OLIVER, N., CURLESS, B., AND SALESIN, D. H. 2001. Image Analogies. In Proc. SIG-GRAPH, 327-340.
14. HURTUT, T., GOUSSEAU, Y., CHERIET, F., AND SCHMITT, F. 2011. Artistic line-drawings retrieval based on the pictorial content. ACM J. Computing and Cultural Heritage 4, 1, 1-23.
15. KALOGERAKIS, E., NOWROUZEZAHRAI, D., BRESLAV, S., AND HERTZMANN, A. 2012. Learning Hatching for Pen-and-Ink Illustration of Surfaces. ACM Trans. Graphics 31, 1:1-1:17.
16. KULIS, B. 2013. Metric learning: A survey. Foundations and Trends in Machine Learning 5, 4, 287-364.
17. LALONDE, J.-F., HOIEM, D., EFROS, A. A., ROTHER, C., WINN, J., AND CRIMINISI, A. 2007. Photo clip art. ACM Trans. Graphics 26, 3, 3:1-3:10.
18. LESSIG, L. 2008. Remix: Making Art and Commerce Thrive in the Hybrid Economy. Penguin Press.
19. LI, C., MEMBER, S., AND CHEN, T. 2009. Aesthetic Visual Quality Assessment of Paintings. IEEE J. Sel. Topics in Signal Processing 3, 2, 236-252.
20. LI, H., ZHANG, H., WANG, Y., CAO, J., SHAMIR, A., AND COHEN-OR, D. 2013. Curve Style Analysis in a Set of Shapes. Computer Graphics Forum 32, 6, 77-88.
21. MCFEE, B., AND LANCKRIET, G. 2011. Learning Multi-modal Similarity. J. Machine Learning Research 12, 491-523.
22. MURRAY, N., BARCELONA, D., MARCHESOTTI, L., AND PER-RONNIN, F. 2012. AVA: A Large-Scale Database for Aesthetic Visual Analysis. In Proc. CVPR, 2408-2415.
23. O'DONOVAN, P., LIBEKS, J., AGARWALA, A., AND HERTZMANN, A. 2014. Exploratory Font Selection Using Crowd-sourced Attributes. ACM Trans. Graphics 33.
24. OJALA, T., PIETIKÄINEN, M., AND MÄENPÄÄ, T. 2002. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. PAMI 24, 7, 971-987.
25. PARIKH, D., AND GRAUMAN, K. 2011. Relative attributes. In Proc. ICCV, 503-510.
26. RADLINSKI, F., BENNETT, P. N., CARTERETTE, B., AND JOACHIMS, T. 2009. Redundancy, Diversity and Interdependent Document Relevance. SIGIR Forum 43, 2.
27. SCHULTZ, M., AND JOACHIMS, T. 2003. Learning a Distance Metric from Relative Comparisons. In Proc. NIPS.
28. SHAMIR, L., MACURA, T., ORLOV, N., ECKLEY, D. M., AND GOLDBERG, I. G. 2010. Impressionism, Expressionism, Surrealism: Automated Recognition of Painters and Schools of Art. ACM Trans. Applied Perception 7, 2, 8:1-8:17.
29. TAMUZ, O., LIU, C., BELONGIE, S., SHAMIR, O., AND KALAI, A. 2011. Adaptively Learning the Crowd Kernel. In Proc. ICML, 673-680.
30. TENENBAUM, J. B., AND FREEMAN, W. T. 2000. Separating Style and Content with Bilinear Models. Neural Computation 12, 6, 1247-1283.
31. VAN DER MAATEN, L., AND HINTON, G. E. 2008. Visualizing High-Dimensional Data Using t-SNE. J. Machine Learning Research 9, 2579-2605.
32. WELINDER, P., BRANSON, S., BELONGIE, S., AND PERONA, P. 2010. The Multidimensional Wisdom of Crowds. In Proc. NIPS, 2424-2432.
33. WILLATS, J., AND DURAND, F. 2005. Defining pictorial style: Lessons from linguistics and computer graphics. Axiomathes 15, 3, 319-351.
34. ZHU, C., BYRD, R. H., LU, P., AND NOCEDAL, J. 1997. Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization. ACM Trans. on Mathematical Software 23, 4.
35. ZHU, C., BICHOT, C.-E., AND CHEN, L. 2010. Multi-scale Color Local Binary Patterns for Visual Object Classes Recognition. In Proc. ICPR, 3065-3068.