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Multi-Camera Object Tracking via Deep Metric Learning

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Multi Camera Object Tracking via Deep Metric Learning

Transferring Representation to ‘Top View’ based on deep metric learning image image image image image image

Visualization of 'top view' by applying PCA on learned embeddings.

demo video on EPFL dataset

For inference:

Download data and trained model from data and trained model, put them in ../box2vec/data and ../box2vec/model directory respectively

Download test videos "4 people indoor sequence"(4p-c0.avi, 4p-c1.avi, 4p-c2.avi, 4p-c3.avi) from “EPFL” data set: Multi-camera Pedestrian Videos and detection files (4p-c0.pickle, 4p-c1.pickle, 4p-c2.pickle,4p-c3.pickle) from detection file for demo. The detection file contain detection result from detector, so that you can run without detector. Create directory ../data/train/lab, put videos and pickle files in it. run

        python3 master.py

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Multi-Camera Object Tracking via Deep Metric Learning


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