These tools create an alpha channel that tells the tracker what areas of the image to ignore and exclude from tracking and calculations. When doing the auto track, it is important that you mask out any objects in the scene that are creating extraneous motion using the masking tools in the 3D tracking application.
By comparing and triangulating the position of points referenced in multiple images (as seen in Figure 4.29), or consecutive frames of a motion image, the position of those points, as well as that of the camera, can be calculated using trigonometry and geometric projections. The origins of 3D tracking technologies lie in the science of photogrammetry, the scientific method of calculating positions and distances of points referenced in one or more images. To be really good at 3D tracking (and to avoid the needless frustration many artists encounter), it’s important to understand how 3D tracking works. If you want to be able to integrate a 3D object into a scene where the camera is moving in three dimensions, you need to be able to re-create this camera’s motion in 3D and have your virtual camera repeating this same motion in order for your element to integrate seamlessly. Unlike 2D tracking, which derives its data from the X and Y motion of pixels on a flat screen, 3D tracking utilizes much more complex triangulation calculations to determine objects’ actual position and motion in 3D space. Figure 4.28 Camera translation close to subject and on an angle so that the 3D nature of the object or subject is revealed.
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