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Carnegie Mellon Robotics Institute

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Abstract

Inferring the depth and shape of remote objects and the camera motion from a sequence of images is possible in principle, but is an ill-conditioned problem when the objects are distant with respect to their size. This problem is overcome by inferring shape and motion without computing depth as an intermediate step. On a single epipolar plane, an image sequence can be represented by the F*P matrix of the image coordinates of P points tracked through F frames. It is shown that under orthographic projection this matrix is of rank three. Using this result, the authors develop a shape-and-motion algorithm based on singular value decomposition. The algorithm gives accurate results, without relying on any smoothness assumption for either shape or motion.

Notes

Text Reference

C. Tomasi and Takeo Kanade, "Shape and Motion without Depth," Proceedings of the Third International Conference on Computer Vision (ICCV '90), December, 1990, pp. 91-95.

BibTeX Reference

@inproceedings{Kanade_1990_1187,
   author = "C. Tomasi and Takeo Kanade",
   title = "Shape and Motion without Depth",
   booktitle = "Proceedings of the Third International Conference on Computer Vision (ICCV '90)",
   pages = "91-95",
   month = "December",
   year = "1990",
}

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