The machine vision market is booming and still needs to be explored in the future

  The application of vision and hearing in machines has brought together the wonderful ideas of many great scientists and has led to some small achievements. At the beginning of the 20th century, movies evolved from silent to sound. It took the efforts of many inventors, including Edison, to realize the storage, release and transmission of sound waves on powerless devices. However, until a hundred years later, machine vision and machine hearing were still a hard nut. There are still many places where machine vision needs to be applied, and there is a constant need to develop and explore.

Floor quality inspection applications, supermarket loss prevention applications, parasite identification, etc. are only preliminary applications of machine vision. From the perspective of AI, machine vision has great potential for development. Drones, unmanned vehicles, and robot navigation are all inseparable from three-dimensional vision. Technology, it is very meaningful to engage in cutting-edge scientific research in this field.
Machine vision technology accelerates drone shooting.
The main application of gesture selfies of intelligent drones is the recognition function of machine vision, and secondly the positioning function. Motion capture technology involves data that can be directly understood and processed by computers in terms of size measurement, positioning and orientation determination of objects in physical space. As movies and games continue to develop, the application of motion capture technology has become more mature.

Machine vision and motion capture technology are equivalent to giving machines a human visual system. UAV gesture selfies are only a very small application of machine vision and motion capture technology. Currently, there are not many drone companies and products that master this technology. The more typical one is DJI. Their Phantom 4 series and Mavic all have the function of gesture selfie. The newly released P4A also has the function of gesture selfie. It seems that DJI has completely mastered this technology and uses it. of perfection.
Machine vision assists autonomous driving
Currently, visual sensors and machine vision technology are widely used in various advanced assisted driving systems. Among them, the perception of the driving environment is one of the important components of advanced assisted driving systems based on machine vision.
The perception of the driving environment mainly relies on visual technology to perceive the road information, road condition information and driver status when the vehicle is driving, and provides the basic data necessary for decision-making for the assisted driving system. Among them,
road information mainly refers to the static information outside the vehicle, including: lane lines, road edges, traffic signs and traffic lights, etc.; road condition
information mainly refers to dynamic information outside the vehicle, including: obstacles in front of the vehicle, pedestrians, vehicles, etc. ;
The driver status belongs to the in-car information, which mainly includes: driver fatigue, abnormal driving behavior, etc. By reminding the driver of possible unsafe behaviors, it can avoid vehicle safety accidents and use machine vision technology to sense the driving environment and obtain it
. Various static and dynamic information inside and outside the car help the assisted driving system make decisions.
Machine vision technology makes robots more stable.
Machine vision is an important direction for the development of robots. It is one of the key factors to improve the intelligence level of robots and helps to realize the automation of robot work.
Robots usually rely on various contact and non-contact sensors to perceive the environment. Machine vision is developed from a bionic perspective. For example, simulated eyes collect images through visual sensors, and after acquisition, the image processing system performs image processing and Identify. In addition, robots with machine vision can sense changes in the external environment in a timely manner, and facilitate the intelligent robot's control system to make corresponding adjustments, improving the robot's flexibility and adaptability to changes in the external environment.