法国INRIA的Fisher向量实现INRIA's Fisher vector implementation
INRIA's Fisher vector implementation
What is this?
This is a Matlab implementation of the Fisher processing chain used in- Aggregating local image descriptors into compact codes Hervé Jégou; Florent Perronnin; Matthijs Douze; Jorge Sánchez; Patrick Pérez; Cordelia Schmid, PAMI 2011.
- Combining attributes and Fisher vectors for efficient image retrieval, Matthijs Douze; Arnau Ramisa; Cordelia Schmid, CVPR 2011.
How to use
You will need:
- Matlab on Linux or Mac OS X (making it work with Octave requires some work).
- A recent version of Yael.
- This package.
- These image descriptors for the Holidays dataset
- These datafiles (centroid files, PCA matrices).
- If you want to compute SIFT descriptors for your own images, you will need compute_descriptors (linux and mac versions). This page explains how to preprocess images before extracting descriptors.
http://lear.inrialpes.fr/src/inria_fisher/inria_fisher_v1.tgz tar xvzf inria_fisher_v1.tgz cd inria_fisher_v1 wget http://lear.inrialpes.fr/src/inria_fisher/inria_fisher_data_v1.tgz tar xvzf inria_fisher_data_v1.tgz wget http://pascal.inrialpes.fr/data/holidays/siftgeo.tar.gz tar xzf siftgeo.tar.gz mkdir -p yael/matlab cd yael/matlab wget https://gforge.inria.fr/frs/download.php/30399/yael_matlab_linux64_v277.tar.gz tar xvzf yael_matlab_linux64_v277.tar.gz cd ../..Then run
test_fisher
in Matlab. This computes Fisher descriptors (k=64) for the Holidays dataset (from the local descriptors in siftgeo/). Then it performs exact NN-searches with the L2 distance on the Holidays query images. After about 10 minutes, it should display:
Fisher k=64 4096D mAP = 0.599 Fisher + PCA (D'=128) 128D mAP = 0.561These numbers correspond to the 59.5 and 56.5 figures in Table I of the PAMI paper (the implementation is not exactly the same).
The PQ compression is not implemented in this version. GMM learning is implemented in Yael but not interfaced in Matlab. Dense descriptors local are implemented in compute_descriptors (-dense option) but no corresponding GMM is provided yet. You may be interested in this package, that also implements compression with PQ codes (on different descriptors).
What to cite
If you use the package in a publication, please cite@article{JEGOU-2011-633013,
url = {http://hal.inria.fr/inria-00633013},
title = {{Aggregating local image descriptors into compact codes}},
author = {J{\'e}gou, Herv{\'e} and Perronnin, Florent and Douze, Matthijs and S{\'a}nchez, Jorge and P{\'e}rez, Patrick and Schmid, Cordelia},
publisher = {IEEE},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2011},
pdf = {http://hal.inria.fr/inria-00633013/PDF/jegou\_aggregate.pdf},
}
Contact, license
If the package does not work, you may complain tomatthijs dot douze at inria dot fr.It is licensed under Cecill , similar to the GPL. Please note that some techniques (eg. SIFT and Fisher) may be covered by non-INRIA software patents.
Last modification on 2012-04-09 by Matthijs Douze.
from: https://lear.inrialpes.fr/src/inria_fisher/