Purpose

Baseline methods for object tracking simply compute IoU over consecutive frames to track objects detected by bounding boxes.
Here I tried to use the feature map associated with each bounding boxes instead, as a proof of concept. I took the time to document each parts of the code, which coupled with the simplicity of the task might make it a good introductory example to deep learning.

Result example from a random youtube video

Setup

This will download ~200Mb of example data, ~100Mb of example results and a bit of code. You could run the script in a bare ubuntu docker image, or in your virtual environment of choice.

./setup.sh

Usage

Open the jupyter notebook (how to install jupyter) Tracking_using_feature_maps.ipynb for details about the method.

TODO

• Dockerize
• Add one command script to track objects