English

Partial 3D Object Retrieval using Local Binary QUICCI Descriptors and Dissimilarity Tree Indexing

Computer Vision and Pattern Recognition 2021-07-29 v1

Abstract

A complete pipeline is presented for accurate and efficient partial 3D object retrieval based on Quick Intersection Count Change Image (QUICCI) binary local descriptors and a novel indexing tree. It is shown how a modification to the QUICCI query descriptor makes it ideal for partial retrieval. An indexing structure called Dissimilarity Tree is proposed which can significantly accelerate searching the large space of local descriptors; this is applicable to QUICCI and other binary descriptors. The index exploits the distribution of bits within descriptors for efficient retrieval. The retrieval pipeline is tested on the artificial part of SHREC'16 dataset with near-ideal retrieval results.

Keywords

Cite

@article{arxiv.2107.03368,
  title  = {Partial 3D Object Retrieval using Local Binary QUICCI Descriptors and Dissimilarity Tree Indexing},
  author = {Bart Iver van Blokland and Theoharis Theoharis},
  journal= {arXiv preprint arXiv:2107.03368},
  year   = {2021}
}

Comments

19 pages, 17 figures, to be published in Computers & Graphics

R2 v1 2026-06-24T03:58:28.899Z