Course Description

Unlock the spatial intelligence behind AI vision systems.

This beginner-friendly course focuses exclusively on camera pose estimation — the key to connecting 2D images with real-world 3D environments. Whether you’re building AR apps, flying drones, or preparing for autonomous systems, learning how to determine a camera’s position and orientation is where it all begins.

🎓 No prior 3D vision experience needed — just your curiosity and a Python-ready mindset.

Camera Pose Estimation for AI Vision Systems gives you a hands-on pathway to mastering spatial awareness in visual computing. You’ll start from scratch — understanding coordinate frames, capturing data, and estimating camera movement from images — and gradually build up to industry-grade techniques used in AR, robotics, and visual SLAM.

In this practical course, you will:

• Understand camera translation and rotation principles
• Explore key pose algorithms like Perspective-n-Point (PnP)
• Work with feature detection and matching (ORB, SIFT)
• Implement pose estimation from real-world video and images
• Visualize pose using 3D axes overlays and transformation maps
• Debug and improve accuracy using common evaluation metrics

This course is perfect for engineers, developers, and curious learners stepping into the exciting world of spatial AI. It lays the groundwork for future topics like 3D reconstruction, SLAM, and neural rendering.