Abstract
With dozens or even hundreds of photos in today's digital photo albums, editing an entire album can be a daunting task. Existing automatic tools operate on individual photos without ensuring consistency of appearance between photographs that share content. In this paper, we present a new method for consistent editing of photo collections. Our method automatically enforces consistent appearance of images that share content without any user input. When the user does make changes to selected images, these changes automatically propagate to other images in the collection, while still maintaining as much consistency as possible. This makes it possible to interactively adjust an entire photo album in a consistent manner by manipulating only a few images.
Our method operates by efficiently constructing a graph with edges linking photo pairs that share content. Consistent appearance of connected photos is achieved by globally optimizing a quadratic cost function over the entire graph, treating user-specified edits as constraints in the optimization. The optimization is fast enough to provide interactive visual feedback to the user. We demonstrate the usefulness of our approach using a number of personal and professional photo collections, as well as internet collections.
Supplemental Material
Available for Download
Supplemental material.
- Agarwal, S., Snavely, N., Simon, I., Seitz, S. M., and Szeliski, R. 2009. Building Rome in a day. In Proc. IEEE ICCV.Google Scholar
- An, X., and Pellacini, F. 2010. User-controllable color transfer. Computer Graphics Forum 29, 2, 263--271.Google Scholar
Cross Ref
- Barnes, C., Shechtman, E., Finkelstein, A., and Goldman, D. B. 2009. PatchMatch: a randomized correspondence algorithm for structural image editing. ACM Trans. Graph. 28, 3. Google Scholar
Digital Library
- Barnes, C. 2011. PatchMatch: A Fast Randomized Matching Algorithm with Application to Image and Video. PhD thesis, Princeton University. Google Scholar
Digital Library
- Bychkovsky, V., Paris, S., Chan, E., and Durand, F. 2011. Learning photographic global tonal adjustment with a database of input/output image pairs. In Proc. IEEE CVPR. Google Scholar
Digital Library
- Caicedo, J. C., Kapoor, A., and Kang, S. B. 2011. Collaborative personalization of image enhancement. In Proc. IEEE CVPR. Google Scholar
Digital Library
- Dale, K., Johnson, M. K., Sunkavalli, K., Matusik, W., and Pfister, H. 2009. Image restoration using online photo collections. In Proc. IEEE ICCV.Google Scholar
- Faktor, A., and Irani, M. 2012. "Clustering by Composition" - unsupervised discovery of image categories. In Proc. ECCV (7), 474--487. Google Scholar
Digital Library
- Farbman, Z., and Lischinski, D. 2011. Tonal stabilization of video. ACM Trans. Graph. 30, 4, 89:1--89:9. Google Scholar
Digital Library
- Frahm, J.-M., Georgel, P. F., Gallup, D., Johnson, T., Raguram, R., Wu, C., Jen, Y.-H., Dunn, E., Clipp, B., and Lazebnik, S. 2010. Building Rome on a cloudless day. In Proc. ECCV (4), vol. 6314, 368--381. Google Scholar
Digital Library
- Gould, S., and Zhang, Y. 2012. PATCHMATCHGRAPH: building a graph of dense patch correspondences for label transfer. In Proc. ECCV, vol. Part V, 439--452. Google Scholar
Digital Library
- HaCohen, Y., Shechtman, E., Goldman, D. B., and Lischinski, D. 2011. Non-rigid dense correspondence with applications for image enhancement. ACM Trans. Graph. 30, 4, 70:1--70:9. Google Scholar
Digital Library
- Hasinoff, S. W., Jóźwiak, M., Durand, F., and Freeman, W. T. 2010. Search-and-replace editing for personal photo collections. In Proc. ICCP.Google Scholar
- Joshi, N., Matusik, W., Adelson, E. H., and Kriegman, D. J. 2010. Personal photo enhancement using example images. ACM Trans. Graph. 29, 2 (April), 12:1--12:15. Google Scholar
Digital Library
- Kagarlitsky, S., Moses, Y., and Hel Or, Y. 2009. Piecewise-consistent color mappings of images acquired under various conditions. In Proc. ICCV, 2311--2318.Google Scholar
Cross Ref
- Kang, S. B., Kapoor, A., and Lischinski, D. 2010. Personalization of image enhancement. In Proc. IEEE CVPR.Google Scholar
- Kim, K. I., Tompkin, J., Theobald, M., Kautz, J., and Theobalt, C. 2012. Match graph construction for large image databases. In Proc. ECCV. Google Scholar
Digital Library
- Laffont, P.-Y., Bousseau, A., Paris, S., Durand, F., and Drettakis, G. 2012. Coherent intrinsic images from photo collections. ACM Trans. Graph. 31, 6, 202:1--11. Google Scholar
Digital Library
- Levin, A., Lischinski, D., and Weiss, Y. 2004. Colorization using optimization. ACM Trans. Graph. 23, 3, 689--694. Google Scholar
Digital Library
- Lowe, D. G. 2004. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 2, 91--110. Google Scholar
Digital Library
- Oskam, T., Hornung, A., Sumner, R. W., and Gross, M. H. 2012. Fast and stable color balancing for images and augmented reality. In 3DIMPVT, IEEE, 49--56. Google Scholar
Digital Library
- Pitié, F., Kokaram, A. C., and Dahyot, R. 2007. Automated colour grading using colour distribution transfer. Comput. Vis. Image Underst. 107 (July), 123--137. Google Scholar
Digital Library
- Reinhard, E., Ashikhmin, M., Gooch, B., and Shirley, P. 2001. Color transfer between images. IEEE Comput. Graph. Appl. (September). Google Scholar
Digital Library
- Sivic, J., and Zisserman, A. 2003. Video Google: A text retrieval approach to object matching in videos. In Proc. IEEE ICCV, 1470. Google Scholar
Digital Library
- Snavely, N., Seitz, S. M., and Szeliski, R. 2006. Photo tourism: exploring photo collections in 3D. ACM Trans. Graph. 25 (July), 835--846. Google Scholar
Digital Library
- Snavely, N., Garg, R., Seitz, S. M., and Szeliski, R. 2008. Finding paths through the world's photos. ACM Trans. Graph. 27, 3, 11--21. Google Scholar
Digital Library
- van de Weijer, J., Gevers, T., and Gijsenij, A. 2007. Edge-based color constancy. IEEE Trans. Im. Proc. 16, 9, 2207--2214. Google Scholar
Digital Library
- Yücer, K., Jacobson, A., Hornung, A., and Sorkine, O. 2012. Transfusive image manipulation. ACM Trans. Graph. 31, 6, 176:1--176:9. Google Scholar
Digital Library
Index Terms
Optimizing color consistency in photo collections
Recommendations
Geo-referenced Tourist Attraction Photo Tagging by Mining Community Photo Collections
Advances in Multimedia Information Processing – PCM 2013AbstractThe advent of photo sharing sites like Flickr has drastically increased the volume of community photo collections on the web. Also the rising popularity of the mobile devices with GPS cameras like iPhone has made most of the photos geo-tagged. ...
Estimating heights from photo collections: a data-driven approach
COSN '14: Proceedings of the second ACM conference on Online social networksA photo can potentially reveal a tremendous amount of information about an individual, including the individual's height, weight, gender, ethnicity, hair color, skin condition, interests, and wealth. A {\em photo collection} -- a set of inter-related ...





Comments