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3D Object Recognition by Indexing Structural Invariants from Multiple Views

Rakesh Mohan, Daphna Weinshall, Ramesh R. Sarukkai
ICCV 1993 pp. 264-268
doi:10.1109/ICCV.1993.378208 /iccv/1993/mohan1993iccv-d/

Abstract

The authors present a method for 3-D object recognition from 2-D image sequences. The system uses feature points tracked over three or more views to compute structural invariants, which serve as 3-D shape representations. Object recognition is performed by using these Euclidean invariants as indices into a high-dimensional shape table. The use of indexing eliminates any need for matching models to images. In addition, the representation of 3-D objects is extracted from 2-D views, eliminating the cumbersome burden of having to obtain 3-D models. The proposed scheme was implemented using a mixed database of real and simulated objects. Experiments are outlined that show good recognition results on real objects and simulated objects corrupted with noise.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Text

Mohan et al. "3D Object Recognition by Indexing Structural Invariants from Multiple Views." IEEE/CVF International Conference on Computer Vision, 1993. doi:10.1109/ICCV.1993.378208

Markdown

[Mohan et al. "3D Object Recognition by Indexing Structural Invariants from Multiple Views." IEEE/CVF International Conference on Computer Vision, 1993.](https://mlanthology.org/iccv/1993/mohan1993iccv-d/) doi:10.1109/ICCV.1993.378208

BibTeX

@inproceedings{mohan1993iccv-d,
  title     = {{3D Object Recognition by Indexing Structural Invariants from Multiple Views}},
  author    = {Mohan, Rakesh and Weinshall, Daphna and Sarukkai, Ramesh R.},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {1993},
  pages     = {264-268},
  doi       = {10.1109/ICCV.1993.378208},
  url       = {https://mlanthology.org/iccv/1993/mohan1993iccv-d/}
}