OpenCV Python with Classical Computer Vision Theory

Currently Playing: OpenCV Python Optical Flow Object Tracking

🎁 Get FREE Robotics & AI Resources (Guide, Textbooks, Courses, Resume Template, Code & Discounts) – Sign up via the pop-up at https://kevinwoodrobotics.com/ 📝 Real-World Robotics Project Course Overview and Waitlist: https://forms.gle/xu4rfk7GWHCaZGBEA 🦾 Learn Robotics and AI: https://kevinwoodrobotics.com/product/all-courses-bundle-deal/ 🤝 Consulting and Mentorship: https://kevinwoodrobotics.com/product-category/consulting/ 👁️ Learn OpenCV: https://kevinwoodrobotics.com/product/opencv-python-tutorials-full-playlist/ 🤖 Learn ROS: https://kevinwoodrobotics.com/product/ros2-tutorials-full-playlist/ 🧠 Learn Computer Vision using AI: https://kevinwoodrobotics.com/product/computer-vision-using-ai/ 🖥️ Learn AI and Machine Learning: https://kevinwoodrobotics.com/product/ai-and-machine-learning-bundle/ 🛒 Amazon Store (My Top Picks for Robot Projects and More!): https://www.amazon.com/shop/kevinwoodroboticsai?ref_=cm_sw_r_cp_ud_aipsfshop_Q3AMRNBSVVB00Y1XR9TN_3 ☕ Support My Channel: https://buymeacoffee.com/kevinwoodrobotics/ In this video, I will go over how to do optical flow object tracking in OpenCV using python in VS Code. Optical flow can be used to do sparse or dense tracking of points. The sparse method uses Lucas Kanade and the dense method uses Gunnar Farneback. 0:00 Introduction 0:21 What is optical flow? 0:48 Why do we need optical flow? 1:02 How does optical flow work? 2:53 Code Thanks for watching! If you found this video helpful, please like, subscribe and share: https://www.youtube.com/@kevinwoodrobotics Social: LinkedIn: https://www.linkedin.com/in/kevinwoodrobotics Github: https://github.com/kevinwoodrobotics LinkedIn: https://www.linkedin.com/in/kevinwoodrobotics Github: https://github.com/kevinwoodrobotics Instagram: https://www.instagram.com/kevinwoodrobotics/ Twitter: https://twitter.com/kevinwoodrobotics