So in this video, Im going to give to you a clear and simple explanation on how Deep SORT works and why its so amazing compared to other models in this computer vision lecture. We implement this in OpenCV in the following course:

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But to understand how DeepSORT works, we first have to go back, waaay back and understand the fundamentals of object tracking and the key innovations that had to happen along the way, for DeepSORT to emerge.

Now tracking assumes that we have an already detected an object of interest. For detection as you may already know is done with YOLOv4. Once we have detected the object, it is assigned an id and is tracked using Deep SORT. We use an example with Elon Musk and SpaceX

So in this application, we have applied deep sort for tracking of vehicles on a highway for traffic surveillance applications.
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0:00 - Introduction
0:42 - Object Tracking
2:39 - Optical Flow and Mean Shift
3:01 - Mean Shift
3:58 - Optical Flow
5:10 - Kalman Filter
7:00 - Simple Online Realtime Tracking (SORT)
7:55 - Detection
8:21 - Estimation
9:00 - Target Association
9:31 - Track Identities life Cycle
10:30 - DeepSORT
11:27 - Deep Learning
12:13 - The Appearance feature Vector
13:03 - Climax of the Story

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