@article{,
title= {Market-1501 Dataset},
journal= {},
author= {},
year= {},
url= {https://web.archive.org/web/20160928141838/http://www.liangzheng.org/Project/project_reid.html},
abstract= {The Market-1501 dataset is collected in front of a supermarket in Tsinghua University. A total of six cameras are used, including 5 high-resolution cameras, and one low-resolution camera. Overlap exists among different cameras. Overall, this dataset contains 32,668 annotated bounding boxes of 1,501 identities. In this open system, images of each identity are captured by at most six cameras. We make sure that each annotated identity is present in at least two cameras, so that cross-camera search can be performed. The Market-1501 dataset has three featured properties:

First, our dataset employes Deformable Part Model (DPM) as pedestrian detector.
Second, in addition to the true positive bounding boxes, we also provde false alarm detection results.
Third, each identify may have multiple images under each camera. During cross-camera search, there are multiple queries and multiple ground truths for each identity.

The Market-1501 dataset is annotated using the following rules. For each detected bounding box to be annotated, we manually draw a ground truth bounding box that contains the pedestrian. Then, for the detected and hand-drawn bounding boxes, we calculate the ratio of the overlapping area to the union area. If the ratio is larger than 50%, the DPM bounding box is marked as "good"; if the ratio is smaller than 20%, the bounding boxe is marked as "distractor"; otherwise, it is marked as "junk", meaning that this image is of zero influence to the re-identification accuracy.

1) "bounding_box_test". There are 19,732 images in this folder used for testing.
2) "bounding_box_train". There are 12,936 images in this folder used for training.
3) "query". There are 750 identities. We randomly select one query image for each camera. So the maximum number of query images is 6 for an identity. In total, there are 3,368 query images in this folder.
4) "gt_query". This folder contains the ground truth annotations. For each query, the relevant images are marked as "good" or "junk". "junk" has zero impact on search accuracy. "junk" images also include those in the same camera with the query.
5) "gt_bbox". We also provide the hand-drawn bounding boxes. They are used to judge whether a DPM bounding box is good.
    
Dataset statistics:
- identities: 1501 (+1 for background).
- images: 12936 (train) + 3368 (query) + 15913 (gallery).
	

```
@inproceedings{zheng2015scalable,
  title={Scalable Person Re-identification: A Benchmark},
  author={Zheng, Liang and Shen, Liyue and Tian, Lu and Wang, Shengjin and Wang, Jingdong and Tian, Qi},
  booktitle={Computer Vision, IEEE International Conference on},
  year={2015}
}
```
},
keywords= {},
terms= {},
license= {},
superseded= {}
}