ML Anthology

Optimised KD-Trees for Fast Image Descriptor Matching

Chanop Silpa-Anan, Richard I. Hartley
CVPR 2008
doi:10.1109/CVPR.2008.4587638 /cvpr/2008/silpaanan2008cvpr-optimised/

Abstract

In this paper, we look at improving the KD-tree for a specific usage: indexing a large number of SIFT and other types of image descriptors. We have extended priority search, to priority search among multiple trees. By creating multiple KD-trees from the same data set and simultaneously searching among these trees, we have improved the KD-tree's search performance significantly. We have also exploited the structure in SIFT descriptors (or structure in any data set) to reduce the time spent in backtracking. By using Principal Component Analysis to align the principal axes of the data with the coordinate axes, we have further increased the KD-tree's search performance.

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Cite

Text

Silpa-Anan and Hartley. "Optimised KD-Trees for Fast Image Descriptor Matching." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587638

Markdown

[Silpa-Anan and Hartley. "Optimised KD-Trees for Fast Image Descriptor Matching." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/silpaanan2008cvpr-optimised/) doi:10.1109/CVPR.2008.4587638

BibTeX

@inproceedings{silpaanan2008cvpr-optimised,
  title     = {{Optimised KD-Trees for Fast Image Descriptor Matching}},
  author    = {Silpa-Anan, Chanop and Hartley, Richard I.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2008},
  doi       = {10.1109/CVPR.2008.4587638},
  url       = {https://mlanthology.org/cvpr/2008/silpaanan2008cvpr-optimised/}
}