ML Anthology

Recovering 3D Motion of Multiple Objects Using Adaptive Hough Transform

Tina Yu Tian, Mubarak Shah
ICCV 1995 pp. 284-289
doi:10.1109/ICCV.1995.466928 /iccv/1995/tian1995iccv-recovering/

Abstract

Presents a method to determine the 3D motion of multiple objects from two perspective views. In our method, segmentation is determined based on a 3D rigidity constraint. We divide the input image into overlapping patches, and for each sample of the translation parameter space, we compute the rotation parameters of patches using a least-squares fit. Every patch votes for a sample in the translation and rotation parameter space. For a patch containing multiple motions, we use an M-estimator to compute rotation parameters of a dominant motion. We use the adaptive Hough transform to refine the relevant parameter space in a "coarse-to-fine" fashion. Applications of the proposed method to both synthetic and real images are demonstrated with promising results.< <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

Tian and Shah. "Recovering 3D Motion of Multiple Objects Using Adaptive Hough Transform." IEEE/CVF International Conference on Computer Vision, 1995. doi:10.1109/ICCV.1995.466928

Markdown

[Tian and Shah. "Recovering 3D Motion of Multiple Objects Using Adaptive Hough Transform." IEEE/CVF International Conference on Computer Vision, 1995.](https://mlanthology.org/iccv/1995/tian1995iccv-recovering/) doi:10.1109/ICCV.1995.466928

BibTeX

@inproceedings{tian1995iccv-recovering,
  title     = {{Recovering 3D Motion of Multiple Objects Using Adaptive Hough Transform}},
  author    = {Tian, Tina Yu and Shah, Mubarak},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1995},
  pages     = {284-289},
  doi       = {10.1109/ICCV.1995.466928},
  url       = {https://mlanthology.org/iccv/1995/tian1995iccv-recovering/}
}