“Paint selection” by Liu, Sun and Shum

  • ©Jiangyu Liu, Jian Sun, and Heung-Yeung Shum




    Paint selection



    In this paper, we present Paint Selection, a progressive painting-based tool for local selection in images. Paint Selection facilitates users to progressively make a selection by roughly painting the object of interest using a brush. More importantly, Paint Selection is efficient enough that instant feedback can be provided to users as they drag the mouse. We demonstrate that high quality selections can be quickly and effectively “painted” on a variety of multi-megapixel images.


    1. Adobe Photoshop. http://www.adobe.com/support/photoshop/.Google Scholar
    2. An, X., and Pellacini, F. 2008. Appprop: all-pairs appearance-space edit propagation. ACM Trans. Graph. 27, 3, 1–9. Google ScholarDigital Library
    3. Bai, X., and Sapiro, G. 2007. A geodesic framework for fast interactive image and video segmentation and matting. In Proceedings of ICCV, 1–8.Google Scholar
    4. Blake, A., Rother, C., Brown, M., Perez, P., and Torr, P. 2004. Interactive image segmentation using an adaptive gmmrf model. In Proceedings of ECCV.Google Scholar
    5. Boykov, Y., and Jolly, M. P. 2001. Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images. In Proceedings of ICCV, 105–112.Google Scholar
    6. Boykov, Y., and Kolmogorov, V. 2001. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. In Energy Minimization Methods in CVPR. Google ScholarDigital Library
    7. Chen, J., Paris, S., and Durand, F. 2007. Real-time edgeaware image processing with the bilateral grid. ACM Trans. Graph. 26, 3, 103. Google ScholarDigital Library
    8. Delong, A., and Boykov, Y. 2008. A scalable graph-cut algorithm for n-d grids. In Proceedings of CVPR, 1–8.Google Scholar
    9. Grady, L. 2006. Random walks for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 28, 11, 1768–1783. Google ScholarDigital Library
    10. Kass, M., Witkin, A., and Terzopoulos, D. 1987. Snakes: Active contour models. IJCV 1, 4, 321–331.Google ScholarCross Ref
    11. Kopf, J., Cohen, M. F., Lischinski, D., and Uyttendaele, M. 2007. Joint bilateral upsampling. ACM Trans. Graph. 26, 3, 96. Google ScholarDigital Library
    12. Levin, A., Lischinski, D., and Weiss, Y. 2008. A closedform solution to natural image matting. IEEE Trans. Pattern Anal. Mach. Intell. 30, 2, 228–242. Google ScholarDigital Library
    13. Li, Y., Sun, J., Tang, C. K., and Shum, H. Y. 2004. Lazy snapping. ACM Trans. Graph. 24, 3, 303–308. Google ScholarDigital Library
    14. Li, Y., Adelson, E. H., and Agarwala, A. 2008. Scribble-boost: Adding classification to edge-aware interpolation of local image and video adjustments. In EGSR. Google ScholarDigital Library
    15. Lischinski, D., Farbman, Z., Uyttendaele, M., and Szeliski, R. 2006. Interactive local adjustment of tonal values. ACM Trans. Graph. 25, 3, 646–653. Google ScholarDigital Library
    16. Lombaert, H., Sun, Y., Grady, L., and Xu, C. 2005. A multilevel banded graph cuts method for fast image segmentation. In ICCV 2005, 259–265. Google ScholarDigital Library
    17. Mortensen, E. N., and Barrett, W. A. 1995. Intelligent scissors for image composition. In Proceedings of ACM SIGGRAPH. Google ScholarDigital Library
    18. Olsen, Jr., D. R., and Harris, M. K. 2008. Edge-respecting brushes. In UIST, 171–180. Google ScholarDigital Library
    19. Reese, L. J. 1999. Intelligent paint: Region-based interactive image segmentation. In Masters Thesis, Department of CS, Brigham Young University, Provo, UT.Google Scholar
    20. Rother, C., Blake, A., and Kolmogorov, V. 2004. Grabcut – interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 24, 3, 309–314. Google ScholarDigital Library
    21. Vineet, V., and Narayanan, P. 2008. Cuda cuts: Fast graph cuts on the gpu. In Proceedings of CVPR Workshops.Google Scholar
    22. Wang, J., and Cohen, M. F. 2005. An iterative optimization approach for unified image segmentation and matting. In Proceedings of ICCV, 936–943. Google ScholarDigital Library
    23. Wang, J., Agrawala, M., and Cohen, M. F. 2007. Soft scissors: an interactive tool for realtime high quality matting. ACM Trans. Graph. 27, 3, 9. Google ScholarDigital Library

ACM Digital Library Publication:

Overview Page: