3-Way-Trees: A Similarity Search Method for High-Dimensional Descriptor Matching

Abstract : In this paper we look into the problem of high-dimensional local descriptor matching for image identification on cultural databases, presenting an important improvement over a classic method, the KD-tree. Our method, the 3-way tree, uses redundant, overlapping sub-trees, in order to avoid the boundary effects that disrupt the KD-tree in higher dimensionalities, achieving more precision for the same querying times.
Document type :
Conference papers
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01336118
Contributor : Lip6 Publications <>
Submitted on : Wednesday, June 22, 2016 - 4:12:52 PM
Last modification on : Thursday, March 21, 2019 - 2:43:07 PM

Identifiers

Citation

Eduardo Valle, Matthieu Cord, Sylvie Philipp-Foliguet. 3-Way-Trees: A Similarity Search Method for High-Dimensional Descriptor Matching. IEEE International Conference on Image Processing (ICIP), Sep 2007, San Antonio, Texas, United States. pp.173-176, ⟨10.1109/ICIP.2007.4378919⟩. ⟨hal-01336118⟩

Share

Metrics

Record views

111