The automotive industry is one of the largest branches of the modern economy. The production of cars, autopilots for cars, parking lot accounting systems is far from a complete list of cases of using computer vision in the automotive industry.
For the correct functioning of the car's autopilot, it is necessary to receive online information about road markings, traffic signs, and the detection of obstacles near the car. Modern recognition and classification algorithms allow on-board computers to navigate without error in the complex conditions of a modern city.
Monitoring and counting of car traffic is an important part of systems for combating car traffic jams in a modern city. With the help of computer vision systems, it is possible to conduct an in-depth analysis of car traffic, counting the number of cars, dividing them into classes, and finding bottle necks in transport systems.
Parking space detection
Tracking the number of occupied parking space is necessary both for accounting for the occupancy of certain spaces and for calculating the expected profit. The use of parking sensors can solve this problem, but the use of a video surveillance camera and a computer vision system allows you to implement the same functionality much cheaper and with better quality.
License plate recognition
Recognition of car license plates has found wide use in our lives, it is also used in automatic speed control systems on roads and accounting for the time spent in a supermarket parking lot. The development of these systems are automatic VIN code reading devices.
One of the most promising options for the application of computer vision in the automotive field is the automatic assessment of car damage. Automatic assessment allows you to get a conclusion about the severity of damage and the approximate cost of repairs without the involvement of an expert. This service allows insurance companies to automate their work and reduce their operating costs.
Driver inattention detection
Continuous driving for a long time tires the driver and dulls his reactions. This leads to an increase in emergency situations on the road. That is why monitoring the driver's condition is an important task, and the use of computer vision to analyze video from the camera makes it possible to determine the degree of driver fatigue as accurately as possible.