Selective Deep Convolutional Features for Image Retrieval
This is the Matlab implements of our methods accepted in ACM MM 2017. [pdf]
This code implements
- The framework of produce global image representation
- Pre-processing: PCA + l2-normalize
- Masking scheme: MAX-mask/SUM-mask
- Embedding: Triangular Embedding (Temb) [1] and Fast Function Approximation Embedding (F-FAemb) [2]
- Aggregating: Democractic pooling [1]
- Post-processing: rotation and whitening, Power-law normalization.
- Extract conv. feature of images
[1] Hervé Jégou and Andrew Zisserman. 2014. Triangulation embedding and democratic aggregation for image search. In CVPR.
[2] Thanh-Toan Do and Ngai-Man Cheung. 2017. Embedding based on function approximation for large scale image search. TPAMI (2017).
BibTex
@INPROCEEDINGS{selectiveDeepConvFea,
author = {Tuan Hoang and Do, Thanh-Toan and Dang-Khoa Le Tan and Cheung, Ngai-Man},
title = {Selective Deep Convolutional Features for Image Retrieval},
bookTitle = {ACM Multimedia},
year = {2017},
month = {Oct},
}
Prerequisites
The code include:
- The Yael library (obtained from the website https://gforge.inria.fr/frs/?group_id=2151) A copy of this library is included in 'tools' folder.
Usage
- Modify the parameters in 'opt.m' file appropriately.
- Run the following script
main
Files and subfolders
| Filename | Description |
|---|---|
| README | This file |
| main.m | The main script for running whole process |
| opt.m | The script contains all parameter setting. |
| extract_feature_map/ | Contains files for extracting conv. features. See the README file inside this folder for more information. |
| tools/ | |
| tools/make.m | Script to build the mex file for faemb and temb methods. |
| tools/democratic/ | contains matlab script files for democratic pooling methods. |
| tools/faemb/ | contains matlab script files for F-FAemb method. |
| tools/faemb_mex/ | contains mex files for F-FAemb method. |
| tools/triemb/ | contains matlab script/mex files for Triangular Embedding method. |
| tools/evaluation/ | contains matlab script files for evaluation. |
| tools/yael/ | contains the yael library |
| utils | --- |
| utils/embedding.m | Process embedding and aggregating |
| utils/apply_mask.m | Compute and then apply mask on the conv. features. |
| utils/crop_qim.m | Crop query images. |
| utils/learn_rn.m | Learn projection (PCA/whitening) matrix |
| utils/vecpostproc.m | Apply post-processing |
| data/ | contains ground truth and data. In case you may want to retrain, please download the provided data and put them in this folder |
| data/workdir/ | contains output files (i.e., parameters, embedded features) |