Matthew Brown
Abstract
Abstract
This paper concerns the problem of fully automated panoramic image stitching. Though the 1D problem (single axis of rotation) is well studied, 2D or multi-row stitching is more difficult. Previous approaches have used human input or restrictions on the image sequence in order to establish matching images. In this work, we formulate stitching as a multi-image matching problem, and use invariant local features to find matches between all of the images. Because of this our method is insensitive to the ordering, orientation, scale and illumination of the input images. It is also insensitive to noise images that are not part of a panorama, and can recognise multiple panoramas in an unordered image dataset. In addition to providing more detail, this paper extends our previous work in the area (Brown and Lowe, 2003) by introducing gain compensation and automatic straightening steps.
- Agarwala, A., Dontcheva, M., Agarwala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M. 2004. Interactive digital photomontage. In ACM Transactions on Graphics (SIGGRAPH'04).Google Scholar
- A multiresolution spline with application to image mosaicsACM Transactions on Graphics19832421723610.1145/245.247Google ScholarDigital Library
- Bascle, B., Blake, A., and Zisserman, A. 1996. Motion deblurring and super-resolution from and image sequence. In Proceedings of the 4th European Conference on Computer Vision (ECCV96). Springer-Verlag, pp. 312–320.Google Scholar
- Beis, J. and Lowe, D. 1997. Shape indexing using approximate nearest-neighbor search in high-dimensional spaces. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR97). pp. 1000–1006.Google Scholar
- Brown, M. and Lowe, D. 2003. Recognising panoramas. In Proceedings of the 9th International Conference on Computer Vision (ICCV03). Nice, vol. 2, pp. 1218–1225.Google Scholar
- Close-range camera calibrationPhotogrammetric Engineering1971378855866Google Scholar
- Brown, M., Szeliski, R., and Winder, S. 2005. Multi-image matching using multi-scale oriented patches. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR05). San Diego.Google Scholar
- Chen, S. 1995. Quick Time VR–-An image-based approach to virtual environment navigation. In SIGGRAPH'95. vol. 29, pp. 29–38.Google Scholar
- Capel, D. and Zisserman, A. 1998. Automated mosaicing with super-resolution zoom. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR98). pp. 885–891.Google Scholar
- Davis, J. 1998. Mosaics of scenes with moving objects. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR98). pp. 354–360.Google Scholar
- Recovering high dynamic range radiance maps from photographsComputer Graphics199731369378Google Scholar
- Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartographyCommunications of the ACM19812438139510.1145/358669.358692618158Google ScholarDigital Library
- Goldman, D.B. and Chen, J.H. 2005 Vignette and exposure calibation and compensation. In Proceedings of the 10th International Conference on Computer Vision (ICCV05). pp. I:899–906.Google Scholar
- Harris, C. 1992. Geometry from visual motion. In Blake, A. and Yuille, A., (eds.), Active Vision. MIT Press, pp. 263–284.Google Scholar
- Huber P.J. 1981. Robust Statistics. Wiley.Google Scholar
- Hartley, R. and Zisserman, A. 2004. Multiple View Geometry in Computer Vision. 2nd edn. Cambridge University Press, ISBN: 0521540518.Google Scholar
- About direct methodsVision Algorithms: Theory and Practice, number 1883 in LNCS1999Corfu, GreeceSpringer-Verlag267277Google Scholar
- Distinctive image features from scale-invariant keypointsInternational Journal of Computer Vision20046029111010.1023/B:VISI.0000029664.99615.94Google ScholarDigital Library
- Meehan, J. 1990. Panoramic Photography. Amphoto Books.Google Scholar
- Computer methods for creating photomosaicsIEEE Transactions on Computers1975C-241111131119Google Scholar
- Image mosaicing using sequential bundle adjustmentImage and Vision Computing2002209–1075175910.1016/S0262-8856(02)00064-1Google ScholarCross Ref
- Microsoft Digital Image Pro. http://www.microsoft.com/products/imaging.Google Scholar
- Linear multi view reconstruction and camera recovery using a reference planeInternational Journal of Computer Vision2002492/31171411012.6876910.1023/A:1020189404787Google ScholarDigital Library
- Realviz. http://www.realviz.com.Google Scholar
- Seetzen, H., Heidrich, W., Stuerzlinger, W., Ward, G., Whitehead, L., Trentacoste, M., Ghosh, A., and Vorozcovs, A. 2004. High dynamic range display systems. In ACM Transactions on Graphics (SIGGRAPH'04).Google Scholar
- Szeliski, R. and Kang, S. 1995. Direct methods for visual scene reconstruction. In IEEE Workshop on Representations of Visual Scenes. Cambridge, MA, pp. 26–33.Google Scholar
- True multi-image alignment and its application to mosaicing and lens distortion correctionIEEE Transactios on Pattern Analysis and Machine Intelligence199921323524310.1109/34.754589Google ScholarDigital Library
- Szeliski, R. and Shum, H. 1997. Creating full view panoramic image mosaics and environment maps. Computer Graphics (SIGGRAPH'97). 31(Annual Conference Series):251–258.Google Scholar
- Construction of panoramic mosaics with global and local alignmentInternational Journal of Computer Vision200036210113010.1023/A:1008195814169Google ScholarDigital Library
- Shi, J. and Tomasi, C. 1994. Good features to track. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR94). Seattle.Google Scholar
- Sivic, J. and Zisserman, A. 2003. Video Google: A text retrieval approach to object matching in videos. In Proceedings of the 9th International Conference on Computer Vision (ICCV03).Google Scholar
- Szeliski, R. 2004. Image alignment and stitching: A tutorial. Technical Report MSR-TR-2004-92, Microsoft Research.Google Scholar
- Bundle adjustment: A modern synthesisVision Algorithms: Theory and Practice, number 1883 in LNCS1999Corfu, GreeceSpringer-Verlag298373Google Scholar
- Bayesian model estimation and selection for epipolar geometry and generic manifold fittingInternational Journal of Computer Vision200250135611012.6877310.1023/A:1020224303087Google ScholarDigital Library
- Uyttendaele, M., Eden, A., and Szeliski, R. 2001. Eliminating ghosting and exposure artifacts in image mosaics. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR01). Kauai, Hawaii, vol. 2, pp. 509–516.Google Scholar
- Zoghlami, I., Faugeras, O., and Deriche, R. 1997. Using geometric corners to build a 2D mosaic from a set of images. In Proceedings of the International Conference on Computer Vision and Pattern Recognition, Puerto Rico. IEEE.Google Scholar
Index Terms
Automatic Panoramic Image Stitching using Invariant Features
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