Abstract
Over the past decade, image mosaicing has become as an important tool for several different areas such as panoramic photography, mapping, scene stabilization, video indexing and compression. Although recent advances in detection of image correspondences have resulted in very good image registration, global alignment is still needed to obtain a globally coherent mosaic. Normally, global alignment requires the non-linear minimization of an error term, which is defined from image correspondences. In this paper, a new global alignment method is presented. It works on the mosaic frame and does not require any non-linear optimization. The proposed method has been tested with several image sequences and comparative results are presented to illustrate its performance.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Szeliski, R., Shum, H.: Creating full view panoramic image mosaics and environment maps. In: SIGGRAPH International Conference on Computer Graphics and Interactive Techniques, Los Angeles, CA, USA, vol. I, pp. 251–258 (1997)
Gracias, N., Costeira, J., Victor, J.: Linear global mosaics for underwater surveying. In: 5th IFAC Symposium on Intelligent Autonomous Vehicles (2004)
Hu, R., Shi, R., Shen, I.F., Chen, W.: Video stabilization using scale-invariant features. In: IV 2007 11th International Conference on Information Visualization, pp. 871–877 (2007)
Irani, M., Anandan, P.: Video indexing based on mosaic representations. Proceedings of the IEEE 86 (1998)
Irani, M., Hsu, S., Anandan, P.: Video compression using mosaic representations. Signal Processing: Image Communication 7, 529–552 (1995)
Capel, D.: Image Mosaicing and Super-resolution. Springer, London (2004)
Kang, E., Cohen, I., Medioni, G.: A graph-based global registration for 2d mosaics. In: International Conference on Pattern Recognition (2000)
Marzotto, R., Fusiello, A., Murino, V.: High resolution video mosaicing with global alignment. In: IEEE Conference on Computer Vision and Pattern Recognition, Washington, DC, USA, vol. I, pp. 692–698 (2004)
Sawhney, H., Hsu, S., Kumar, R.: Robust video mosaicing through topology inference and local to global alignment. In: European Conference on Computer Vision, Freiburg, Germany, vol. II, pp. 103–119 (1998)
Can, A., Stewart, C.V., Roysam, B., Tanenbaum, H.L.: A feature-based technique for joint linear estimation of high-order image-to-mosaic transformations: Mosaicing the curved human retina. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(3), 412–419 (2002)
Cervantes, A., Kang, E.Y.: Progressive multi-image registration based on feature tracking. In: International Conference on Image Processing, Computer Vision, & Pattern Recognition, Las Vegas, pp. 633–639 (2006)
Zitová, B., Flusser, J.: Image registration methods: A survey. Image and Vision Computing 21(11), 977–1000 (2003)
Harris, C.G., Stephens, M.J.: A combined corner and edge detector. In: Alvey Vision Conference, Manchester, U.K., pp. 147–151 (1988)
Beaudet, P.R.: Rotational invariant image operators. In: IAPR International Conference on Pattern Recognition, pp. 579–583 (1978)
Lindeberg, T.: Feature detection with automatic scale selection. International Journal of Computer Vision 30(2), 77–116 (1998)
Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Bay, H., Tuytelaars, T., Van Gool, L.: Surf: Speeded up robust features. In: European Conference on Computer Vision (2006)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(10), 1615–1630
Fischler, M., Bolles, R.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. Assoc. Comp. Mach. 24(6), 381–395 (1981)
Meer, P., Mintz, D., Rosenfeld, A.: Analysis of the least median of squares estimator for computer vision applications. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 621–623 (1992)
Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)
Davis, J.: Mosaics of scenes with moving objects. In: IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, CA, USA, vol. I, pp. 354–360 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Elibol, A., Garcia, R., Delaunoy, O., Gracias, N. (2008). A New Global Alignment Method for Feature Based Image Mosaicing. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_25
Download citation
DOI: https://doi.org/10.1007/978-3-540-89646-3_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89645-6
Online ISBN: 978-3-540-89646-3
eBook Packages: Computer ScienceComputer Science (R0)