This repository hosts the codebase for the following work: Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O., & Radke, R. J. (2016). A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets. IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted February 2018.
Tested on Windows Server 2012 with MATLAB 2016b
- Clone this repository
- Run a quick example in run_experiment_benchmark.m
- Read the results for VIPeR dataset with WHOS feature and XQDA
- 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
- HistLBP
- WHOS
- gBiCov
- LDFV
- ColorTexture\ELF
- LOMO (Windows)
- GOG (Windows)
- 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
- rnp
- srid
- ahisd
- VIPeR Parition included in repo
- Airport Partition comes with dataset
- DukeMTMC4ReID Partition comes with dataset
- Market1501 Partition
- CAVIAR (WHOS feature only) Parition included in repo
- Karanam, S., Gou, M., Wu, Z., Rates-Borras, A., Camps, O., & Radke, R. J. (2016). A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets. IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted February 2018.
- Please also cite the work appropriately for each used feature/metric learning/ranking/dataset