Calculate Occlusion

In any triangulation based 3D vision system occlusion can occur. For guidance on positioning the camera to minimize occlusion in a real setup, see the positioning pages for bin-picking, piece-picking, and depalletization.

Occlusion from Object Height

Occlusion can also occur from the height of an object itself, independent of any bin wall or divider. In the illustration below, the taller blue object hides the shorter orange object.

Whether a tall object occludes its neighbors depends on several factors: where it sits along the camera’s horizontal axis, its height, and its distance from the camera. The camera’s baseline also plays a role.

Occlusion from Multiple Bins

In stationary mounted bin-picking or piece-picking the bin walls or dividers can create this situation. If the camera is looking at two compartments then occlusion can be avoided by aligning the camera baseline with the shared wall or divider. If there are more than two compartments no such alignment is possible. For example:

• picking from more than 2 bins

• picking from a bin with 2 or more dividers

larger baseline ➞ worse occlusion effect

2 bins, negligible occlusion

Top view

Side view

4 bins, unavoidable occlusion

Top view

Side view

The following calculator shows the occlusion effects across a single wall or divider. The camera is positioned directly above the wall such as to minimize the worst case occlusion. You can see that the occlusion is symmetric across the wall.

How does the calculator work?

The calculator computes occlusion as bin_depth * tan(atan(baseline / 2 / distance_to_bin)).

• baseline is the camera’s baseline in mm.

• distance_to_bin is the distance from the camera to the top of the bin in mm.

• bin_depth is the depth of the bin (or divider height) in mm.

The 2D camera and projector each sit offset from the camera’s center by half the baseline. With the camera centered above the shared wall, the one further from a given side is the one whose view over that wall is blocked first, so its offset (half the baseline) sets the occlusion angle on that side. The examples below use this formula directly, with real camera baselines and the calculator’s own AutoStore bin depths.

Camera	Baseline	Bin depth	Distance to top	Occlusion	Note
Zivid 2+	110 mm	200 mm (Small AutoStore)	500 mm	Approximately 22.0 mm	A shorter camera-to-bin distance increases occlusion even with a shallower bin.
Zivid 2+	110 mm	330 mm (Medium AutoStore)	1000 mm	Approximately 18.2 mm
Zivid 3 XL250	250 mm	425 mm (Large AutoStore)	1000 mm	Approximately 53.1 mm	At the same 1000 mm distance, the larger baseline accounts for most of the increase in occlusion from the row above; the deeper bin adds comparatively little on its own.