Abstract
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.
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Levin, A., Lischinski, D., Weiss, Y.: Colorization using optimization. ACM Transactions on Graphics 23, 689 (2004)
Welsh, T., Ashikhmin, M., Mueller, K.: Transferring color to greyscale images. ACM Transactions on Graphics 21(3), 277–280 (2002)
Ironi, R., Cohen-Or, D., Lischinski, D.: Colorization by example. In: Rendering Techniques, pp. 201–210 (2005)
Charpiat, G., Hofmann, M., Schölkopf, B.: Automatic Image Colorization Via Multimodal Predictions. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 126–139. Springer, Heidelberg (2008)
Tai, Y.W., Jia, J., Tang, C.K.: Local color transfer via probabilistic segmentation by expectation-maximization. In: Computer Vision and Pattern Recognition, vol. 1, pp. 747–754. IEEE (2005)
Chia, A.Y.S., Zhuo, S., Gupta, R.K., Tai, Y.W., Cho, S.Y., Tan, P., Lin, S.: Semantic colorization with internet images. ACM Transactions on Graphics 30(6), 1–8 (2011)
Arnheim, R.: Art and visual perception: A psychology of the creative eye. University of California Press (1954)
Kobayashi, S.: Color image scale. Kosdansha International (1991)
Kobayashi, S.: Art of Color Combinations. Kosdansha International (1995)
Reinhard, E., Adhikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Computer Graphics and Applications 21(5), 34–41 (2001)
Chen, T., Cheng, M.M., Tan, P., Shamir, A., Hu, S.M.: Sketch2photo: internet image montage. ACM Transactions on Graphics 28(5), 124:1–124:10 (2009)
Cohen-Or, D., Sorkine, O., Gal, R., Leyvand, T., Xu, Y.Q.: Color harmonization. ACM Transactions on Graphics 25(3), 624–630 (2006)
O’Donovan, P., Agarwala, A., Hertzmann, A.: Color compatibility from large datasets. ACM Transactions on Graphics 30(4), 63:1–63:12 (2011)
Rother, C., Kolmogorov, V., Blake, A.: ”GrabCut”: interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics 23(3), 309–314 (2004)
Cheng, M.M., Zhang, F.L., Mitra, N.J., Huang, X., Hu, S.M.: Repfinder: finding approximately repeated scene elements for image editing. ACM Transactions on Graphics 29, 83:1–83:8 (2010)
Cheng, M.M., Zhang, G.X., Mitra, N.J., Huang, X., Hu, S.M.: Global contrast based salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 409–416. IEEE (June 2011)
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(4), 509–522 (2002)
Wang, X.H., Jia, J., Cai, L.H.: Affective image adjustment with a single word. To apper in The Visual Computer
Dong, Z., Dong, Q.: HowNet and the Computation of Meaning. World Scientific (2006)
Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.B.: Patchmatch: a randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics 28(3), 24:1–24:11 (2009)
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Wang, X., Jia, J., Liao, H., Cai, L. (2012). Image Colorization with an Affective Word. In: Hu, SM., Martin, R.R. (eds) Computational Visual Media. CVM 2012. Lecture Notes in Computer Science, vol 7633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34263-9_7
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DOI: https://doi.org/10.1007/978-3-642-34263-9_7
Publisher Name: Springer, Berlin, Heidelberg
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