In recent years, 3D cameras have become important in industrial and consumer applications. Technicians have used 3D imaging technology to develop 3D scanners and other equipment that are widely used in various industries. Machine vision systems with 3D imaging capabilities can inspect components on the production site faster and more accurately. In the consumer field, 3D cameras provide greater image depth for the media.

3D camera inspired by the most sophisticated imaging device: the eye

3D imaging relies on stereoscopic photography, which we can observe from a familiar source: the human 

visual system. Humans see things with two eyes slightly separated. This allows them to perceive depth in 

addition to the horizontal and vertical information reproduced by, for example, a standard 2D TV screen.

Since the eyes are separate, each person sees the world from a different perspective. Quickly covering 

one eye, then the other, each time reveals a subtle but noticeable difference in perspective. The 

dimensionality that humans perceive in vision comes from the brain combining different images into a 

whole - a phenomenon called parallax.

Every 3D shot uses two lenses - each lens captures an image slightly offset from the other. Therefore, a 

3D image contains twice as much information as a 2D image. The images are edited for display while main

taining full data fidelity. The eye cannot process two sets of images on its own: each eye processes its 

own set of images.

How to implement 3D camera imaging?

3D cameras can be used for a wide range of applications - analyzing, measuring and locating parts are the

most important. However, to achieve the best results, it is crucial to design a system with the necessary 

performance and environmental constraints.

3D camera imaging can be achieved through active or passive methods. Active systems use methods such

 as time of flight, structured light and interferometry, which usually require a high degree of control in the 

shooting environment. Passive methods include depth of focus and light field.

In snapshot-based methods, the difference between two snapshots captured at the same time is used to 

calculate the distance to the object - this is called passive stereo imaging. This can be achieved by moving

 a single camera, but using two cameras with the same specifications is more efficient.

In contrast, active snapshot methods can incorporate other techniques to interpret the visual data. Active 

snapshots can use time of flight to encode 3D data into each pixel by measuring the time it takes for light 

to travel to the target object and then return to the sensor.

Another successful method for generating 3D shape data is laser triangulation. In laser triangulation, a sing

le camera is used to derive height changes from laser patterns projected onto the surface of the object, 

and then observe how these patterns move when viewed from the camera's perspective. Even with a singlcamera and without triangulation, it is still possible to get a sense of object distance by observing how 

objects scale as they move closer or farther away from the camera.

Whatever the method used, the result is reliable visualization data that can be used to improve the 

performance of critical processes, especially in industry.