ML Anthology

A Unifying Framework for Structure and Motion Recovery from Image Sequences

Philip F. McLauchlan, David William Murray
ICCV 1995 pp. 314-320
doi:10.1109/ICCV.1995.466923 /iccv/1995/mclauchlan1995iccv-unifying/

Abstract

The paper proposes a statistical framework that enables 3D structure and motion to be computed optimally from an image sequence, on the assumption that feature measurement errors are independent and Gaussian distributed. The analysis and results demonstrate that computing both camera/scene motion and 3D structure is essential to computing either with any accuracy. Having computed optimal estimates of structure and motion over a small number of initial images, a recursive version of the algorithm (previously reported) recomputes sub optimal estimates given new image data. The algorithm is designed explicitly for real time implementation, and the complexity is proportional to the number of tracked features. 3D projective, affine and Euclidean models of structure and motion recovery have been implemented, incorporating both point and line features into the computation. The framework can handle any feature type and camera model that may be encapsulated as a projection equation from scene to image.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

McLauchlan and Murray. "A Unifying Framework for Structure and Motion Recovery from Image Sequences." IEEE/CVF International Conference on Computer Vision, 1995. doi:10.1109/ICCV.1995.466923

Markdown

[McLauchlan and Murray. "A Unifying Framework for Structure and Motion Recovery from Image Sequences." IEEE/CVF International Conference on Computer Vision, 1995.](https://mlanthology.org/iccv/1995/mclauchlan1995iccv-unifying/) doi:10.1109/ICCV.1995.466923

BibTeX

@inproceedings{mclauchlan1995iccv-unifying,
  title     = {{A Unifying Framework for Structure and Motion Recovery from Image Sequences}},
  author    = {McLauchlan, Philip F. and Murray, David William},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1995},
  pages     = {314-320},
  doi       = {10.1109/ICCV.1995.466923},
  url       = {https://mlanthology.org/iccv/1995/mclauchlan1995iccv-unifying/}
}