Due to the limitations of technology, the plane images obtained by ordinary cameras have created huge restrictions on the machine's understanding of the surrounding environment. Now, due to the emergence of 3D depth cameras, machines have also acquired 3D vision capabilities, allowing machines to recognize and understand the surrounding environment. A leap has taken place improvement. Artificial intelligence needs to rely on the development of computational vision to acquire and recognize external visual information. So today there are 3D depth cameras in the most popular fields such as robot navigation, autonomous driving, drones, AR/VR/MR, 3D reconstruction, human-computer interaction, and intelligent manufacturing.
With the popularity of machine vision, autonomous driving, and robots, the use of 3D depth cameras to collect depth information of the environment, and then to perform object recognition, environment modeling and other applications is becoming more and more common.
Compared with the traditional 2D camera, the 3D camera adds a one-dimensional depth of breath, so it can better describe the real world. This has very important application value in many fields, such as security, surveillance, machine vision, robotics, etc. It also expands more technical solutions for these businesses, such as object recognition and obstacle detection in autonomous driving, scattered in industry Object recognition, sorting, shelf grabbing of objects in logistics scenes, etc. are all inseparable from the extraction of object contours.
