Huiwen Chang will present her General Exam April 30, 2015 at 1pm in CS401. The members of her committee are: Adam Finkelstein (adviser), Jianxiong Xiao, Thomas Funkhouser. Everyone is invited to attend her talk, and those faculty wishing to remain for the oral exam following are welcome to do so. Her abstract and reading list follow below. Abstract: Color manipulation is a key process in photo enhancement, and professional image editing suites incorporate an array of tools to support it. Some of these tools are easy to understand but offer a limited range of expressiveness. Other more powerful tools are difficult and time consuming to use, and inscrutable to novices. Researchers have described a variety of more sophisticated methods but these are typically not interactive, which is crucial for creative exploration. This paper introduces a simple, intuitive and interactive tool that allows non-experts to recolor an image colors by editing a color palette. This system is comprised of several components: a GUI that is easy to learn and understand, a new efficient algorithm for creating a color palette from an image, and a new efficient color transfer algorithm that recolors the image based on a user-modified palette. We evaluate our approach via a user study, showing that it is faster and easier to use than two alternatives. It also shows that untrained users can quickly achieve results comparable to those of experts using professional software. Reading List: Bychkovsky, V., Paris, S., Chan, E., & Durand, F. (2011, June). Learning photographic global tonal adjustment with a database of input/output image pairs. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on (pp. 97-104). IEEE. Cohen-Or, D., Sorkine, O., Gal, R., Leyvand, T., & Xu, Y. Q. (2006, July). Color harmonization. In ACM Transactions on Graphics (TOG) (Vol. 25, No. 3, pp. 624-630). ACM. Lin, S., & Hanrahan, P. (2013, April). Modeling how people extract color themes from images. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3101-3110). ACM. Lin, S., Ritchie, D., Fisher, M., & Hanrahan, P. (2013). Probabilistic color-by-numbers: Suggesting pattern colorizations using factor graphs. ACM Transactions on Graphics (TOG) , 32 (4), 37. Shapira, L., Shamir, A., & Cohen‐Or, D. (2009, April). Image Appearance Exploration by Model‐Based Navigation. In Computer Graphics Forum (Vol. 28, No. 2, pp. 629-638). Blackwell Publishing Ltd. Wang, B., Yu, Y., Wong, T. T., Chen, C., & Xu, Y. Q. (2010, December). Data-driven image color theme enhancement. In ACM Transactions on Graphics (TOG) (Vol. 29, No. 6, p. 146). ACM. Wang, X., Jia, J., & Cai, L. (2013). Affective image adjustment with a single word. The Visual Computer , 29 (11), 1121-1133. Tai, Y. W., Jia, J., & Tang, C. K. (2005, June). Local color transfer via probabilistic segmentation by expectation-maximization. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on (Vol. 1, pp. 747-754). IEEE. O'Donovan, P., Agarwala, A., & Hertzmann, A. (2011, August). Color compatibility from large datasets. In ACM Transactions on Graphics (TOG) (Vol. 30, No. 4, p. 63). ACM. Chang, Y., Saito, S., Uchikawa, K., & Nakajima, M. (2006). Example-based color stylization of images. ACM Transactions on Applied Perception , 2 (3), 322-345. Kanungo, T., Mount, D. M., Netanyahu, N. S., Piatko, C. D., Silverman, R., & Wu, A. Y. (2002). An efficient k-means clustering algorithm: Analysis and implementation. Pattern Analysis and Machine Intelligence, IEEE Transactions on , 24 (7), 881-892. Hearn, D. D., Baker, M. P., & Carithers, W. (2010). Computer graphics with open gl . Prentice Hall Press.