Shape and Motion Without Depth

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.<<ETX>>

Cite

Text

Tomasi and Kanade. "Shape and Motion Without Depth." IEEE/CVF International Conference on Computer Vision, 1990. doi:10.1109/ICCV.1990.139501

Markdown

[Tomasi and Kanade. "Shape and Motion Without Depth." IEEE/CVF International Conference on Computer Vision, 1990.](https://mlanthology.org/iccv/1990/tomasi1990iccv-shape/) doi:10.1109/ICCV.1990.139501

BibTeX

@inproceedings{tomasi1990iccv-shape,
  title     = {{Shape and Motion Without Depth}},
  author    = {Tomasi, Carlo and Kanade, Takeo},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1990},
  pages     = {91-95},
  doi       = {10.1109/ICCV.1990.139501},
  url       = {https://mlanthology.org/iccv/1990/tomasi1990iccv-shape/}
}