3D depth cameras can be used for a wide range of applications.it is the most important part to analyze, measure and locate. However, to obtain the best results, it is critical to design a system with the necessary performance and environmental constraints.
3D depth camera imaging can be achieved through active or passive methods. Active systems use methods such as tof sensors, structured light, etc., which often 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 it is more efficient to use two cameras with the same specs.
In contrast, active snapshot methods can incorporate other techniques for interpreting visual data. Activity snapshots can use a tof sensor, which encodes 3D data into each pixel by measuring the elapsed time when light travels to the target object and then back to the sensor.
Another successful method for generating 3D shape data is laser triangulation. In laser triangulation, a single camera is used to derive height changes from laser patterns projected onto the surface of an object, and then to observe how these patterns move when viewed from the camera’s perspective. Even with a single camera and no triangulation, object distance can still be sensed by seeing how objects scale as they approach or move away from the camera.
3D depth camera work regardless of the method, the result is reliable visualization data that can be used to improve the performance of critical processes, especially in industry.
