Image sensors are gradually developing from 2D to 3D. The introduction of depth information makes the scalability of applications such as smartphones, automobiles, and AR become higher and higher. Moving from 2D to 3D is a major trend in the development of sensors in the future.
Many machine vision applications require high-resolution 3D depth camera to replace or augment standard 2D map imaging. Such solutions rely on 3D depth camera to provide reliable depth information for safety, especially when machines work in close proximity to people.3D depth camera also need to provide reliable depth information when working in challenging environments, such as those with moving objects.
Due to the rapid emergence of 3D tof cameras, 3D tof cameras are often used as data acquisition devices in real-time systems for 3D reconstruction applications.
In robotic applications,3D depth cameras are mainly used in three aspects: precise secondary positioning of robotic arms, personnel following, and robotic arm obstacle avoidance. Two of them are briefly described below:
3D depth camera is a new technology emerging in recent years. Compared with the traditional camera, 3D depth camera adds a depth measurement to the function, which makes it more convenient and accurate to perceive the surrounding environment and changes.
The application of depth camera is in the fields of intelligent human-computer interaction, face technology, 3D reconstruction, robotics, AR and other fields. At present, the most mature application of commercial depth camera is a variety of interesting applications based on face technology on mobile terminals.
3D ToF camera can measure the distance directly. The figure below is a schematic diagram of the Phab2 pro mobile phone's rear 3D ToF camera measuring in three-dimensional space.
Common RGB-D cameras with rough intrinsic and extrinsic calibration data are often unable to meet the accuracy requirements required for many robotics applications. Our calibration method is based on a novel two-component measurement error model that unifies the error sources of RGB-D cameras based on different technologies, such as structured light 3D cameras and time-of-flight cameras
The accuracy of ToF sensor depends on its pulse duration. Compared with binocular vision and structured light schemes, ToF sensor accuracy does not decrease significantly with distance. d-ToF is a key technology for long-distance applications.
Face recognition is a biometric identification technology based on human facial feature information. A series of related technologies that use tof camera to collect images or video streams containing faces, and automatically detect and track faces in the images, and then perform face recognition on the detected faces, also known as portrait recognition and face recognition.
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