3DEqualizer

City environment tracking

We started by tracking a wide exterior shot of a city environment. The focus here was on identifying stable points across buildings and architectural elements, which allowed us to reconstruct the scene in 3D space. This gave us a clearer understanding of how the camera moves through the environment and how depth can be translated from a flat image into a spatial layout.

Rebuilding space in 3D

After tracking the footage, we switched to the 3D view and placed simple geometry, such as cubes, into the scene. These were used as rough stand-ins for buildings, helping us visualise scale, perspective, and spatial relationships. This step made the tracking feel more tangible, turning abstract points into a readable structure.

Background tracking on character footage

In the second session, we worked with footage of a man walking through an urban setting. We began by tracking background points to establish a stable base for the shot. This created a solid foundation before introducing any elements that needed to follow the subject more closely.

Once the background was set, we moved on to tracking the man’s face. This allowed us to explore more detailed tracking and understand how smaller, more precise points could be used to drive CG elements attached directly to a person, rather than the environment.

Iron Man mask placement

With the facial tracking in place, we imported a 3D Iron Man mask into 3DEqualizer and aligned it to the tracked points. This step focused on adjusting the scale and position of the mask and checking that it moved convincingly with the subject throughout the shot.

Export to Maya

The final step was exporting the tracked camera, footage, and data into Maya. This allowed us to further adjust the mask in a 3D scene, refine its placement, and check how well it sat within the shot. Bringing everything into Maya helped connect the tracking process to a full CG workflow and a finished visual result.

The result: