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Systematic Design of Indexing Strategies for Object Recognition

Andrea Califano, Rakesh Mohan
CVPR 1993 pp. 709-710
doi:10.1109/CVPR.1993.341017 /cvpr/1993/califano1993cvpr-systematic/

Abstract

The authors analyze how parameters of indexing based recognition systems affects their performance. The main result is that increasing the dimensionality of the indices leads to significantly improved discrimination, false positive suppression and reduced recognition times. With increase in index dimensionality, coarser quantization is required to allow index match in the presence of noise. The authors' analysis also allows estimation of votes thresholds for recognition and estimation of the amount of occlusion that can be tolerated by indexing schemes for given levels of recognition confidence.< <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

Califano and Mohan. "Systematic Design of Indexing Strategies for Object Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.341017

Markdown

[Califano and Mohan. "Systematic Design of Indexing Strategies for Object Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/califano1993cvpr-systematic/) doi:10.1109/CVPR.1993.341017

BibTeX

@inproceedings{califano1993cvpr-systematic,
  title     = {{Systematic Design of Indexing Strategies for Object Recognition}},
  author    = {Califano, Andrea and Mohan, Rakesh},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {709-710},
  doi       = {10.1109/CVPR.1993.341017},
  url       = {https://mlanthology.org/cvpr/1993/califano1993cvpr-systematic/}
}