Peter Pesti
ABSTRACT
Commercial aerial imagery websites, such as Google Maps, MapQuest, Microsoft Virtual Earth, and Yahoo! Maps, provide high- seamless orthographic imagery for many populated areas, employing sophisticated equipment and proprietary image postprocessing pipelines. There are many areas of the world with poor coverage where locals might benefit from recent, high-resolution orthographic imagery, but which do not fit into the schedules and scaling model of the big sites.
This paper describes MapStitcher, a system that orthorectifies and geographically registers imagery using only low-cost capturing equipment. MapStitcher combines manually-entered relationships between images and known ground references with a MOPs-based image-stitching technique that automatically discovers image-to-image relationships. Our image registration pipeline first extracts and matches feature points, then clusters images, then uses RANSAC-initialized bundle adjustment to simultaneously optimize all constraints over the entire image set. Simultaneous optimization balances the requirements of precise stitching and absolute placement accuracy. We used this technique to image a portion of the Skagit River Valley in the vicinity of the town of Concrete, WA (pop. 790) at 0.15 m/pixel. Our technique is more accurate than stitching followed by "rubber-sheeting" (deforming the stitched image into global coordinates), while it also requires less effort and produces a better-stitched composite than rubber-sheeting images separately.
- M. Brown and D. G. Lowe. Unsupervised 3D object recognition and reconstruction in unordered datasets. In 3DIM, pages 56--63. IEEE Computer Society, 2005. Google Scholar
Digital Library
- M. Brown and D. G. Lowe. Automatic panoramic image stitching using invariant features. International Journal of Computer Vision, 74(1):59--73, Aug. 2007. Google ScholarDigital Library
- M. Brown, R. Szeliski, and S. Winder. Multi-image matching using multi-scale oriented patches. In CVPR, pages 510--517. IEEE Computer Society, 2005. Google ScholarDigital Library
- B. A. DeWitt and P. R. Wolf. Elements of Photogrammetry (with Applications in GIS). McGraw-Hill Higher Education, 2000. Google ScholarDigital Library
- J. Elson, J. Howell, and J. R. Douceur. Mapcruncher: integrating the world's geographic information. Operating Systems Review, 41(2):50--59, 2007. Google ScholarDigital Library
- M. A. Fischler and R. C. Bolles. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM, 24(6):381--395, 1981. Google ScholarDigital Library
- R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, ISBN: 0521540518, second edition, 2004. Google ScholarDigital Library
- F. A. V. D. Heuvel. Exterior orientation using coplanar parallel lines. Proceedings of the 10th Scandinavian Conference on Image Analysis, pages 71--78, 1997.Google Scholar
- F. A. V. D. Heuvel. Estimation of interior orientation parameters from constraints on line measurements in a single image. International Archives of Photogrammetry and Remote Sensing, 32:81--88, 1999.Google Scholar
- V. Kwatra, A. Schödl, I. A. Essa, G. Turk, and A. F. Bobick. Graphcut textures: image and video synthesis using graph cuts. ACM Trans. Graph, 22(3):277--286, 2003. Google ScholarDigital Library
- S. Mahamud, M. Hebert, Y. Omori, and J. Ponce. Provably-convergent iterative methods for projective structure from motion. In CVPR, pages 1018--1025. IEEE Computer Society, 2001.Google ScholarCross Ref
- P. F. McLauchlan and A. Jaenicke. Image mosaicing using sequential bundle adjustment. Image Vision Comput, 20(9--10):751--759, 2002.Google Scholar
- L. Quan and Z.-D. Lan. Linear N-point camera pose determination. IEEE Trans. Pattern Anal. Mach. Intell, 21(8):774--780, 1999. Google ScholarDigital Library
- B. Vandeportaele, C. Dehais, M. Cattoen, and P. Marthon. ORIENT-CAM, A camera that knows its orientation and some applications. In J. F. M. Trinidad, J. A. Carrasco-Ochoa, and J. Kittler, editors, CIAPR, volume 4225 of Lecture Notes in Computer Science, pages 267--276. Springer, 2006. Google ScholarDigital Library
Index Terms
- Low-cost orthographic imagery
Recommendations
Low-cost 360 stereo photography and video capture
A number of consumer-grade spherical cameras have recently appeared, enabling affordable monoscopic VR content creation in the form of full 360° X 180° spherical panoramic photos and videos. While monoscopic content is certainly engaging, it fails to ...
Parallax-Aware Image Stitching Based on Homographic Decomposition
Pattern RecognitionAbstractImage stitching plays a crucial role for various computer vision applications, like panoramic photography, video production, medical imaging and satellite imagery. It makes it possible to align two images captured at different views onto a single ...
A Fourier Approach to Camera Orientation
Recovering camera orientation with respect to a known coordinate system is of great significance to photogrammetry and binocular stereo. In binocular stereo, the relative orientation between a camera pair may be obtained from the orientation of each ...
Comments