“Photographing long scenes with multi-viewpoint panoramas” by Agarwala, Agrawala, Cohen, Salesin and Szeliski

We present a system for producing multi-viewpoint panoramas of long, roughly planar scenes, such as the facades of buildings along a city street, from a relatively sparse set of photographs captured with a handheld still camera that is moved along the scene. Our work is a significant departure from previous methods for creating multi-viewpoint panoramas, which composite thin vertical strips from a video sequence captured by a translating video camera, in that the resulting panoramas are composed of relatively large regions of ordinary perspective. In our system, the only user input required beyond capturing the photographs themselves is to identify the dominant plane of the photographed scene; our system then computes a panorama automatically using Markov Random Field optimization. Users may exert additional control over the appearance of the result by drawing rough strokes that indicate various high-level goals. We demonstrate the results of our system on several scenes, including urban streets, a river bank, and a grocery store aisle.

1. Agarwala, A., Dontcheva, M., Agrawala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M. 2004. Interactive digital photomontage. ACM Transactions on Graphics 23, 3, 294–302. Google ScholarDigital Library
2. Agarwala, A., Zheng, K. C., Pal, C., Agrawala, M., Cohen, M., Curless, B., Salesin, D. H., and Szeliski, R. 2005. Panoramic video textures. ACM Transactions on Graphics 24, 3 (Aug.), 821–827. Google ScholarDigital Library
3. Agrawala, M., Zorin, D., and Munzner, T. 2000. Artistic multiprojection rendering. In Rendering Techniques 2000: 11th Eurographics Workshop on Rendering, 125–136. Google ScholarDigital Library
4. Astola, J., Haavisto, P., and Neuvo, Y. 1990. Vector median filters. Proceedings of the IEEE 78, 678–689.Google ScholarCross Ref
5. Bertalmio, M., Sapiro, G., Caselles, V., and Ballester, C. 2000. Image inpainting. In Proceedings of ACM SIGGRAPH 2000, Computer Graphics Proceedings, Annual Conference Series, 417–424. Google ScholarDigital Library
6. Boykov, Y., Veksler, O., and Zabih, R. 2001. Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 11, 1222–1239. Google ScholarDigital Library
7. Brown, M., and Lowe, D. G. 2005. Unsupervised 3D object recognition and reconstruction in unordered datasets. In 3D Imaging and Modeling (3DIM ’05), 55–63. Google ScholarDigital Library
8. Davis, J. 1998. Mosaics of scenes with moving objects. In Computer Vision and Pattern Recognition (CVPR 98), 354–360. Google ScholarDigital Library
9. ePaperPress, 2005. http://epaperpress.com/ptlens/.Google Scholar
10. Google, 2005. http://earth.google.com.Google Scholar
11. Gupta, R., and Hartley, R. I. 1997. Linear pushbroom cameras. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 9, 963–975. Google ScholarDigital Library
12. Hartley, R. I., and Zisserman, A. 2004. Multiple View Geometry in Computer Vision, second ed. Cambridge University Press. Google ScholarDigital Library
13. Huber, P. 1981. Robust statistics. John Wiley.Google Scholar
14. Kang, S. B., Szeliski, R., and Chai, J. 2001. Handling occlusions in dense multi-view stereo. In Computer Vision and Pattern Recognition (CVPR 2001), vol. 1, 103–110.Google Scholar
15. Kasser, M., and Egels, Y. 2002. Digital Photogrammetry. Taylor & Francis Inc. Google ScholarDigital Library
16. Koller, M., 2004. http://www.seamlesscity.com.Google Scholar
17. Kolmogorov, V., and Zabih, R. 2002. What energy functions can be minimized via graph cuts? In European Conference on Computer Vision (ECCV), 65–81. Google ScholarDigital Library
18. Kubovy, M. 1986. The psychology of perspective and renaissance art. Cambridge University Press.Google Scholar
19. Kwatra, V., Schödl, A., Essa, I., Turk, G., and Bobick, A. 2003. Graphcut textures: Image and video synthesis using graph cuts. ACM Transactions on Graphics 22, 3, 277–286. Google ScholarDigital Library
20. Levin, G., 2005. An informal catalogue of slit-scan video artworks. http://www.flong.com/writings/lists/list_slit_scan.html.Google Scholar
21. Levoy, M., Chen, B., Vaish, V., Horowitz, M., McDowall, I., and Bolas, M. 2004. Synthetic aperture confocal imaging. ACM Transactions on Graphics 23, 3 (Aug.), 825–834. Google ScholarDigital Library
22. Lowe, D. 2004. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 2, 91–110. Google ScholarDigital Library
23. Mitsunaga, T., and Nayar, S. K. 1999. Radiometric self calibration. In Computer Vision and Pattern Recognition (CVPR ’99), 374–380.Google Scholar
24. Peleg, S., Rousso, B., Rav-Acha, A., and Zomet, A. 2000. Mosaicing on adaptive manifolds. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 10, 1144–1154. Google ScholarDigital Library
25. Pérez, P., Gangnet, M., and Blake, A. 2003. Poisson image editing. ACM Transactions on Graphics 22, 3, 313–318. Google ScholarDigital Library
26. Rademacher, P., and Bishop, G. 1998. Multiple-center-of-projection images. In Proceedings of SIGGRAPH 98, Computer Graphics Proceedings, Annual Conference Series, 199–206. Google ScholarDigital Library
27. Rav-Acha, A., Shor, Y., and Peleg, S. 2004. Mosaicing with parallax using time warping. In 2004 Computer Vision and Pattern Recognition Workshop (CVPRW’04), vol. 11. Google ScholarDigital Library
28. Roman, A., Garg, G., and Levoy, M. 2004. Interactive design of multi-perspective images for visualizing urban landscapes. In Proceedings of IEEE Visualization, 537–544. Google ScholarDigital Library
29. Seitz, S. M., and Kim, J. 2003. Multiperspective imaging. IEEE Computer Graphics & Applications 23, 6, 16–19. Google ScholarDigital Library
30. Snavely, N., Seitz, S., and Szeliski, R. 2006. Photo tourism: exploring photo collections in 3D. ACM Transactions on Graphics 25, 3, To appear. Google ScholarDigital Library
31. Sun, J., Yuan, L., Jia, J., and Shum, H.-Y. 2005. Image completion with structure propagation. ACM Transactions on Graphics 24, 3 (Aug.), 861–868. Google ScholarDigital Library
32. Szeliski, R., and Shum, H.-Y. 1997. Creating full view panoramic mosaics and environment maps. In Proceedings of SIGGRAPH 97, Computer Graphics Proceedings, Annual Conference Series, 251–258. Google ScholarDigital Library
33. Uyttendaele, M., Eden, A., and Szeliski, R. 2001. Eliminating ghosting and exposure artifacts in image mosaics. In Computer Vision and Pattern Recognition (CVPR 01), 509–516.Google Scholar
34. Wexler, Y., and Simakov, D. 2005. Space-time scene manifolds. In International Conference on Computer Vision (ICCV’05), vol. 1, 858–863. Google ScholarDigital Library
35. Wood, D. N., Finkelstein, A., Hughes, J. F., Thayer, C. E., and Salesin, D. H. 1997. Multiperspective panoramas for cel animation. In Proceedings of SIGGRAPH 97, Computer Graphics Proceedings, Annual Conference Series, 243–250. Google ScholarDigital Library
36. Yu, J., and McMillan, L. 2004. A framework for multiperspective rendering. In Proceedings of the 15th Eurographics workshop on Rendering Techniques, 61–68. Google ScholarDigital Library
37. Yu, J., and McMillan, L. 2004. General linear cameras. In European Conference on Computer Vision (ECCV 04), 14–27.Google ScholarCross Ref
38. Zheng, J. Y. 2003. Digital route panoramas. IEEE MultiMedia 10, 3, 57–67. Google ScholarDigital Library
39. Zomet, A., Feldman, D., Peleg, S., and Weinshall, D. 2003. Mosaicing new views: The crossed-slits projection. IEEE Transactions on PAMI 25, 6, 741–754. Google ScholarDigital Library