MARS-evaluation

This code provides evaluation procedure of the MARS dataset. Please kindly cite the Arxiv paper if you use this dataset.

Liang Zheng*, Zhi Bie*, Yifan Sun*, Jingdong Wang, Chi Su, Shengjin Wang, Qi Tian, \"MARS: A Video Benchmark for Large-Scale Person Re-identification\", ECCV, 2016. (* equal contribution)

This code uses the 1024-dim IDE de or [1] and KISSME [2] and XQDA [3] distance metrics. To run this code, one should follow the three steps below.

1. Download the pre-computed IDE feature: http://pan.baidu.com/s/1mhBrwMG or https://drive.google.com/folderview?id=0B6tjyrV1YrHed3BnZnNaSUs3eEE&usp=sharing. Unzip it in the root folder.

2. Run \"test_mars.m\".

If you want to try your own de or or to learn new features, you should do as follows.

1. Download the dataset: http://pan.baidu.com/s/1hswMDfu or https://drive.google.com/folderview?id=0B6tjyrV1YrHeMVV2UFFXQld6X1E&usp=sharing. Training should be done with images in folder \"bbox_train\".

2. Bounding box feature extraction should follow the order specified in \"root/info/test_name.txt\" and \"root/info/train_name.txt.\" The newly extracted feature should be loaded in line 19-20 in \"root/test_mars.m\"