Learn how to track objects in OpenCV using the HSV color space on the Jetson Nano. Convert images to HSV, set tracking parameters using trackbars, and create foreground and background masks for effective object detection. Explore techniques for troubleshooting, tweaking values, and addressing common challenges in color-based object tracking. Gain hands-on experience with real-time object tracking using a Jetson Nano and camera setup, focusing on red object detection as an example.
AI on the Jetson Nano - Tracking Objects in OpenCV Using HSV Color Space
Overview
Syllabus
Intro
HSV Color Space
Read from Still Image
Track Bars
Convert to HSV
Create lower and upper bounds
Create foreground mask
Troubleshooting
Tweaking Values
Creating Foreground Mask
Creating Background Mask
Background Mask vs Foreground Mask
Background Mask
Final Image
Tracking on Red
The Problem
Taught by
Paul McWhorter
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