  This paper presents the learned techniques during the Video Analysis Module
of the Master in Computer Vision from the Universitat Aut\`onoma de Barcelona,
used to solve the third track of the AI-City Challenge. This challenge aims to
track vehicles across multiple cameras placed in multiple intersections spread
out over a city. The methodology followed focuses first in solving
multi-tracking in a single camera and then extending it to multiple cameras.
The qualitative results of the implemented techniques are presented using
standard metrics for video analysis such as mAP for object detection and IDF1
for tracking. The source code is publicly available at:
https://github.com/mcv-m6-video/mcv-m6-2021-team4.
