Mastering 3D Camera Tracking in Fusion Part 1

January 6, 2026

Learn 3D camera tracking in Fusion from point detection through solve refinement to 3D scene export, with practical testing techniques.


Series

From Point Detection to 3D Scene – How to build and test a robust 3D camera solve

Learn how to set up 3D camera tracking in DaVinci Resolve Fusion. Understand what a good initial point selection looks like and evaluate point-based and global solve errors. Then, after refining the initial track, learn to create a scene export and test your solution in 3D.


If you’ve mastered point tracking and planar tracking in Fusion, 3D camera tracking represents the next frontier – and sometimes, it’s unavoidable. Whether you’re integrating 3D elements into live-action footage or need to paint out defects in shots with complex camera movement, a solid camera solve forms the foundation of successful compositing work.

Achieving a successful composite

However, here’s the challenge: anyone can generate a 3D camera track that appears visually appealing. The real skill lies in creating a track that actually supports compositing – one that allows precise 3D object placement and withstands scrutiny throughout your shot. This Insight guides you through the complete workflow using an example that’s ideal for learning: abundant high-contrast features, significant camera movement, and sufficient complexity to reveal common pitfalls.


“…[to evaluate] how our tracking solution actually interacts with any compositing tasks we want to do afterwards…we [need] the full picture and not just a nice camera track and then stop.”

Bernd Klimm, Compositor
This Insight uses footage you can download for free - and is sufficiently complex that you'll learn while following along.
This Insight uses footage you can download for free – and is sufficiently complex that you’ll learn while following along.

The strategy of 3D Camera Tracking

The workflow begins with strategy. Before auto-tracking a single point, you’ll learn to evaluate your shot for trackability—looking for good contrast spread across the frame and, crucially, across depth. Points clustered on a single plane or concentrated along the horizon won’t give you a usable solve. You need distribution in all three dimensions, particularly in areas where you plan to place elements later.


Key Takeaways

By the end of this Insight, you should understand how to:

  • Configure and run Fusion’s 3D Camera Tracker with optimal point detection settings
  • Iteratively improve your camera solve towards low solve error and quality 3D reference points
  • Evaluate point distribution across both spatial dimensions and depth for maximum solve reliability
  • Create and align a 3D scene with a proper coordinate reference that’s ready for compositing
  • Test your camera solve using checkerboard-textured geometry to verify stability

Mentioned Resources

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