Advanced Technologies & Insights
Computer Vision (CV) has become paramount for the automotive industry’s success today. Empowering cars to detect drivable roads and pedestrians is the norm, computer vision works closely with AI (Artificial Intelligence) to enable the automotive sector to expand and create better end features. As the vast majority of automated tasks rely on advanced visualization and require a certain ability of intelligent systems to detect potential anomalies, Computer Vision comes forth as a key partner of AI, transforming the automotive sector into an even more responsive and autonomous one.
What is Computer Vision?
Computer Vision is a modern interdisciplinary scientific field whose aim is to study ways in which computers can gain a high level of understanding of digital videos and images. Computer Vision is also used to train requisite models for properly detecting, identifying, and classifying images with utmost accuracy. Automatic vehicle manufacturing units and intelligent cars are getting increasingly dependent on Computer Vision setups so that they can better process everything that’s happening inside and outside the vehicle.
The scope of Computer Vision is not just to avert mishaps and accidents, but also to entail manufacturing intelligent vehicles with incremental setups. Some of the key uses of Computer Vision in today’s automotive industry include:
- Quality Assurance: since it’s crucial for manufacturers to ensure the vehicles they create are of utmost quality before going into mass production, they leverage images and video annotation tools powered by Computer Vision to inspect the electronic and safety components of their vehicles.
- Automated manufacturing: most manufacturing warehouses are already leveraging the perks of CV to minimize human exposure and accurately detect new parts and then empower robots to properly pick up and drop each component based on the manufacturing process.
- Intelligent Driving Assistance: one of the key roles of Computer Vision is to enable drivers to stay safe behind their wheels and avoid accidents. This innovative technology leverages built-in sensors to detect roads, vehicles, obstacles, pedestrians, and others, with the purpose of avoiding a collision.
- Enhanced Autonomous Cars: Computer Vision plays a vital role in improving modern autonomous cars, ensuring safer parking, sending out perceptive warnings, performing 3D mapping, enhancing LIDAR orientation for a complete 360-degree analysis of the surrounding environment, and automating airbag deployment in case of a threat.
Applications of Computer Vision in Today’s Vehicles
In addition to the uses presented above, Computer Vision can be used extensively both inside and outside the car. On the inside, it can successfully analyze the expression of the driver to see if he/she is asleep or is falling asleep and then can either stop the car or activate a strong alarm to wake them up. To top it all, it can leverage infrared sensors and temperature sensors to detect if children are trapped inside heating cars.
On the outside, Computer Vision is normally used along with autonomous driving, helping to recognize street signs and street lanes. Advanced systems can utilize multiple cameras to reconstruct a surrounding scene in 3D or can utilize LIDAR to augment a specific image and improve it with geolocation and databases for a complete picture. Thus, Computer Vision can be used alongside regular traffic cams or dashboard cameras to determine the culprit of accidents. Additionally, it can be utilized by the V2X (Vehicles to Everything) to connect to surrounding cars and offer important data to other drivers.
On the same note, using simultaneously location and mapping, cars, robots, and even drones can leverage Computer Vision to accurately plan their routes and navigates in uncharted territories.
What About the Future of CV in Automotive?
Experts agree that Computer Vision will continue to play a key role in the automotive industry by being responsible for adding new safety features to modern vehicles and by protecting passengers. Predictive decision-making and object detection will continue to save lives and become mainstream, being used more and more as part of V2X and smart cities.
Some of the future trends that will shape this field include;
- The usage of cloud computing services that would help scale deep learning solutions
- Innovation of transformer architectures that are used in machine learning and quality assurance & production tasks
- Creation of mobile devices that are tied to the IoT network and enable drivers to gain a better understanding of their external environment
Computer vision will continue to expand and grow, becoming increasingly important in the automotive industry. If you want to learn more about this field, you can contact us at email@example.com.