A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval
This is the official repository for the publication:
@inproceedings{schoenberger2016vote,
author = {Sch\"{o}nberger, Johannes Lutz and Price, True and Sattler, Torsten and Frahm, Jan-Michael and Pollefeys, Marc},
title = {A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval},
booktitle={Asian Conference on Computer Vision (ACCV)},
year={2016},
}
World5k Dataset
The URLs for all images in our dataset can be found in the image_urls
folder.
Vote-and-Verify Code
An implementation of both the vocabulary tree with Hamming embedding as well as
our proposed Vote-and-Verify method can be found in COLMAP
(https://github.com/colmap/colmap). COLMAP is a Structure-from-Motion and Multi-
View Stereo library. COLMAP implements a fully functional image retrieval system
(in the src/retrieval/*
folder), that can be used with the executables:
-
src/exe/vocab_tree_builder
: to build a custom vocabulary tree from image features -
src/exe/vocab_tree_retriever
: to perform image retrieval using a pre-built vocabulary tree -
src/exe/vocab_tree_matcher
: to match images using the vocabulary tree
The number of images to re-rank during spatial verification can be specified
using the num_verifications
option. Please refer to the code and the
documentation of COLMAP for more details and fine-grain control of the
parameters (https://colmap.github.io/).