3D vision-based dimensioners are becoming more popular thanks to their cost-effectiveness and easy-to-deploy nature. As the dimensioning paradigm shifts from primitive ultrasound/infrared sensors and expensive lasers to 3D vision cubing systems, some questions may arise among users.

How Does 3D Vision Dimensioning Differ From Others?

3D cameras capture the distance of their surroundings in a snapshot instead of their colors as regular 2D cameras do. 3D vision-based dimensioners process captured distance frames and extract the object of interest. Then objects dimensions are measured using the distance data. One of the advantages of 3D image processing is that every visible part of the box is taken into account in dimension measurement.

In infrared or ultrasound point-sensor based dimensioners, the dimensions of objects are measured only using 3 point measurements assuming that the object is perfectly rectangular. However, this is never the case; no box is perfectly rectangular.

Laser-based dimensioners also create a 3D representation of objects but they do it by scanning objects line by line instead of in a single image as 3D cameras do and hence they are not suitable for static measurements.

How Does 3D Vision Dimensioning Differ From Others?

Just like other cameras, 3D cameras have a cone-shaped field of view. The objects that are completely in the field of view of cameras can be measured correctly. Hence, the dimensioning capacity of 3D vision dimensioners is bounded by how they can see. Wider objects can be measured if their height is low.
Some vendors prefer to specify the dimensioning range per every edge as in the table below but this can be very misleading for the customers.

The table below does not tell you that your 3D dimensioner can measure 100 x 100 x 100 cm sized object! In fact, it just tells you that the maximum measurable size per edge is 100cm as in 100 x 100 x 10cm and 10 x 10 x 100cm sized objects.