DeepSORT - DEEP LEARNING applied to OBJECT TRACKING | OpenCV Python | Computer Vision |2021

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:

⭐6-in-1 AI Mega Course - https://augmentedstartups.info/AugmentedAICVPRO ⭐FREE DeepSORT+ YOLOv4 Course - https://augmentedstartups.info/yolov4release

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.

Learn Advanced Tutorials ►Augmentedstartups.info/Teachable-AI-Bootcamp Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram

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

---~~~--- ⭐ If you are feeling Gratuitous, I'd really like some Coffee😎☕ - https://augmentedstartups.info/BuyMeCoffee ---~~~--- ... https://www.youtube.com/watch?v=LbyqsoLJu5Q