Visual Information Processing and Learning
Visual Information Processing and Learning


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Occluded-DukeMTMC-VideoReID Database

1.       Overview


Occluded-DukeMTMC-VideoReID is a video person reID dataset on occluded scenes. It is constructed from the DukeMTMC-VideoReID [1] dataset. In the new dataset, all query tracklets are occluded by large variety of occlusion (e.g., trees, cars and other persons), while gallery set contains both holistic and occluded tracklets. It contains 1,702 tracklets covering 702 identities in total, the query set contains 661 tracklets of 661 identities and the gallery set contains 1975 tracklets of 1,110 identities. The figure below gives a few examples of the occluded tracklets.


Figure 1. Sample tracklets of the Occluded-DukeMTMC-VideoReID dataset


2.       Evaluation Protocol

For occluded video person reID task, we recommend using Cumulative Matching Characteristic (CMC) curves and mean Average Precision (mAP) to evaluate the performance.


3.       Contact

Bingpeng Ma (bpma@ucas.ac.cn),University of Chinese Academy of Sciences.

Hong Chang (ChangHong@ict.ac.cn), Institute of Computing Technology, Chinese Academy of Sciences.

Ruibing Hou(ruibing.hou@vipl.ict.ac.cn), Institute of Computing Technology, Chinese Academy of Sciences.


4.       Download

The Occluded-DukeMTMC-VideoReID is released for research purpose only. To request a copy, please access the https://github.com/blue-blue272/Occluded-DukeMTMC-VideoReID-dataset refer to all sources.


References

1.       Y. Wu, Y. Lin, X. Dong, Y. Yan, W. Quyang, and Y. Yang, “Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning,” in IEEE Conference on Computer Vision and Pattern Recognition, pp. 5177–5186, 2018.

 

 


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