# Full Body Tracking and Recognition

**URL:** <https://forum.opencv.org/t/full-body-tracking-and-recognition/5708>\
**Category:** Uncategorized\
**Created:** [October 18, 2021, 7:49pm UTC](https://forum.opencv.org/t/full-body-tracking-and-recognition/5708 "2021-10-18T19:49:39Z")\
**Posts on this page:** 1\
**Showing post:** 4

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**Author:** ![berak](https://avatars.discourse-cdn.com/v4/letter/b/85f322/32.png) [@berak](https://forum.opencv.org/u/berak)\
**Post date:** [October 19, 2021, 1:52pm UTC](https://forum.opencv.org/t/full-body-tracking-and-recognition/5708/4 "2021-10-19T13:52:05Z")

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you’ll find some references [in the original pr](https://github.com/opencv/opencv/pull/19108)

> Zheng F, Deng C, Sun X, et al. Pyramidal person re-identification via multi-loss dynamic training[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 8514-8522.
> 
> Yu F, Jiang X, Gong Y, et al. Devil’s in the Details: Aligning Visual Clues for Conditional Embedding in Person Re-Identification[J]. arXiv e-prints, 2020: arXiv: 2009.05250.

in the end, there a pretrained cnn, you process images through it , and receive a simple 1d feature vector, that can be easily compared with L2 or cosine norm .

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