https://github.com/RSL-NEU/person-reid-benchmark

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets
https://github.com/RSL-NEU/person-reid-benchmark

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A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

• Host: GitHub
• URL: https://github.com/RSL-NEU/person-reid-benchmark
• Owner: RSL-NEU
• License: bsd-3-clause
• Created: 2017-11-22T18:17:06.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-08-14T15:05:53.000Z (about 6 years ago)
• Last Synced: 2024-05-20T20:19:20.655Z (4 months ago)
• Language: HTML
• Size: 45.2 MB
• Stars: 194
• Watchers: 13
• Forks: 77
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Person Re-identification Benchmark

This repository hosts the codebase for the following work:

Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O., & Radke, R. J. (2018). 

[A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.](https://arxiv.org/abs/1605.09653) IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted February 2018.

Tested on Windows Server 2012 with MATLAB 2016b

### Quick Start

* Clone this repository

* Run a quick example in run_experiment_benchmark.m

* Read the results for VIPeR dataset with WHOS feature and XQDA

### Run other experiments

* Download supported dataset, unzip it and put it under the folder ./Data 

* Download corresponding partition file and put it under the folder ./TrainTestSplits

* Run corresponding prepare_DATANAME.m inside the folder ./Data (if avaliable)

* Change the parameters in run_experiment_benchmark.m 

### Check List for supported/tested feature

* HistLBP

* WHOS

* gBiCov

* LDFV

* ColorTexture\ELF

* LOMO (Windows)

* GOG (Windows)

### Check List for supported/tested metric learning

* FDA

* LFDA

* kLFDA-linear/chi2/chi2-rbf/exp

* XQDA

* MFA

* kMFA-linear/chi2/chi2-rbf/exp

* NFST

* KISSME

* PCCA-linear/chi2/chi2-rbf/exp

* rPCCA-linear/chi2/chi2-rbf/exp

* kPCCA-linear/chi2/chi2-rbf/exp

* PRDC

* SVMML

* kCCA

### Check List for supported/tested multi-shot ranking method

* rnp

* srid

* ahisd

### Check List for supported/tested dataset

* [VIPeR](http://users.soe.ucsc.edu/~manduchi/VIPeR.v1.0.zip) Parition included in repo

* [Airport](http://www.northeastern.edu/alert/transitioning-technology/alert-datasets/alert-airport-re-identification-dataset/) Partition comes with dataset

* [DukeMTMC4ReID](http://robustsystems.coe.neu.edu/sites/robustsystems.coe.neu.edu/files/systems/dataset/DukeMTMC4ReID.zip) Partition comes with dataset

* [Market1501](http://www.liangzheng.org/Project/project_reid.html) [Partition](http://robustsystems.coe.neu.edu/sites/robustsystems.coe.neu.edu/files/systems/code/reid_benchmark/partition/Partition_market.mat)

* CAVIAR (WHOS feature only) Parition included in repo

### Reference

Please cite the work appropriately for each used feature/metric learning/ranking/dataset 

```

@ARTICLE{8294254, 

author={S. Karanam and M. Gou and Z. Wu and A. Rates-Borras and O. Camps and R. J. Radke}, 

journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 

title={A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets}, 

year={2018}, 

keywords={Benchmark testing;Cameras;Feature extraction;Histograms;Image color analysis;Measurement;Probes}, 

doi={10.1109/TPAMI.2018.2807450}, 

ISSN={0162-8828}, 

} 

```