How Does Computer Vision Work?
Artificial Intelligence (AI) is extensively used in our everyday life. Its introduction has revolutionized the execution of a variety of processes that were known for their complexity. Computer vision is also a sub-branch of Artificial Intelligence. It is not about image processing, as often people misunderstand how does computer vision work? It is far different from image processing.
Computer vision involves techniques enabling computers to see and interpret visual content for the automation of various processes. Computer vision has revolutionized plenty of industrial processes including manufacturing.
What are Computer Vision Goals and Tasks?
As the use of visual content is increasing day by day. More than half of consumers want to observe more visual content from the brands they like, as conceived by HubSpot. It has become immensely essential to make use of computer vision to handle information from visual content, including images and videos as well.
Simply put, computer vision is employed to mimic natural processes done by a human brain like retrieving information through visual content, handling the data, and interpreting the results for further actions. Though computers are still way behind the capabilities of a human brain in processing visual processing, computer vision is a great step in the right direction.
Computer vision works to perform multiple tasks. These tasks include image classification, semantic segmentation, classification, localization, object detection, object tracking, instance segmentation, action recognition, and image enhancement. These tasks of computer vision work pretty well in combination with each to bring comprehensive results.
How does Computer Vision Method Work in Today`s World?
In this section, we will try to elaborate on how computer vision works in various industries and processes for automation and saving the human effort required for the operation otherwise. Here is a list of some use cases for your reference:
Robotic Manufacturing Processes
As the industry is going through a revolutionary phase while transforming the manufacturing work from manual operations to automated solutions using robotics, computer vision has a lot to do for this cause.
Robotic machines which are employed to handle the manufacturing process and eliminate the need for human effort are using computer vision method. Robots deployed to work in the manufacturing process need to see what is around them for accurate operations.
Robotic machines often inspect entire assembly lines to figure out what is coming for them, this helps them in working at the required pace to perform required operations on every item in assembly tolerance timely.
Check out our Robotic process automation services.
Computer Vision for Vehicles
People are turning towards autonomous solutions in almost every task in their everyday life. Similar is the case with vehicles. After some successful results in testing of self-driving vehicles, almost all the vehicle manufacturers around the world have started their campaign to introduce autonomous vehicles with the capability of self-driving. Leaders in this autonomous vehicle campaign are Tesla and Mercedes.
Tesla is known to be the leader in introducing self-driving vehicles. Here is a link to give more details about self-driving vehicles by Tesla. Mercedes, a renowned vehicle manufacturer, is known for its innovative approach throughout its history, is also introducing self-driving vehicles to have the edge over its competitors, especially BMW.
In addition to self-driving, vehicles are using computer vision as driver assistance systems. The vehicles can assist in the control of speed, steering, and lane switch with the use of computer vision. There is more to come with the passage of time, but we are sure computer vision is helping a lot in working towards totally autonomous vehicles.
Health and Medicine:
The use of computer vision in the medicine industry is already bringing ideal results. Computer vision is used to pipeline cell segmentation in such a way that it can process an image at an individual pixel level. In addition to processing, computer vision is also capable of interpreting the results and identify the spot where rogue cells are present. Computer vision also helps in coloring multiple elements in an object in different colors for more straightforward interpretation.
Update: We have highlighted some greate uses cases of Predictive analytics in healthcare
It is immensely useful in identifying and precisely detecting the root cause of a disease like tumors. Using a conventional way of pathology and medical scanning was quite complicated. It was also observed that medical experts agreed on the diagnosis in less than 48% of the medical cases. However, with the help of AI and computer vision, results are highly accurate. Therefore, medical experts don’t need much effort in brainstorming to diagnose the disease. This ultimately helps them in focusing more on the treatment to eliminate the ailment of patients.
Predictive maintenance is a crucial part of the manufacturing process. The failure of machinery in the middle of this process could bring a lot of embarrassment and bad reputation to the company. This could be a disaster for any company. Therefore, many companies are turning towards Robotic Process Automation (RPA) for this process, which works hand in hand with the computer vision for accurate working and almost zero chance of failure.
Machine learning-powered smart devices use computer vision to monitor incoming data from machinery with the help of sensors. This enables smart devices to identify signals and take proactive actions to avoid any manufacturing disaster.
Inspection of Packages:
Computer vision could also be used for inspection of packages to control the quality of the manufacturing process. This is especially a very beneficial tool for pharmaceutical companies to ensure the right number of tablets and capsules in packing. It could also be a great tool for companies manufacturing spare parts and bearings.
The photos of packages moving through the production line are taken through advanced cameras and sensors. These cameras then deliver these snaps to main control unit which checks the package and counts the tally of items in the package. If an irregularity is identified, the particular package is eliminated from checkout line. This technology could also be used for inspection of packages at airports and ports by the customs department to avoid the delivery of any prohibited item in the country.
Object Detection and Tracking in Sports:
Machine learning and computer vision have become an essential element in sports. Umpires and referees take the help of these technologies during decision referral systems for object detection and object tracking.
The technology also helps in getting knowledge about the performances of players and athletes while performing actions. Computer vision also helps in the post-game analysis as well.
3D Computer Vision:
The 3D computer vision could be employed to analyze the performances of athletes and predict the actions of athletes during a game. 3D vision also allows the building of a 3D point cloud, which is a representation of a 2D image in 3D format. Computers can trace the location and shape of the object after building a 3D point cloud. This technology could also help a lot in forensics.
3D vision is also used in retail for monitoring items without any barcodes scanning process by Amazon. It also helps in healthcare. The process of surgery of patients could be observed in real-time through this technology.
Processing of Visuals for Agriculture:
Precision farming is getting popular day by day. Farmers are finding livestock management solution convenient for various agriculture processes. Many farming industries are making use of satellite images for analysis through computer vision to get precise information about conditions of crops and lands.
AI-led computer vision solutions are also employed in the process of winemaking to ensure the production of finest and disease-free wine and monitor vineyards. Automated drones with high-quality cameras are also deployed to inspect the are to figure out any problem through computer vision.
Computer Vision Powered AR:
Augmented reality has become an essential element in advertising campaigns and industrial procedures. AR made possible through computer vision could help out vehicle manufacturers and various other industries to get a boost in the maintenance and assembly process because of the use of AR.
AR enables industries to make use of the option to implement the application of real-time data integrated with real objects easily.
How Does Folio3 Computer Vision Solution Help Businesses?
Folio3 is known for its progressive approach and helping businesses from various verticals of the industry to bring automation in their industrial processes. The implementation of computer vision in industrial processes by Folio3 is not different. Here are some use cases made possible by our efficient computer vision implementation team for your reference:
Road Traffic Analysis
We took up a challenge to develop a solution for road traffic analysis by incorporating computer vision in the development to craft an excellent road traffic analysis proprietary product. We developed this product after in-depth research to analyze the road and traffic situation with the help of AI.
Our solution is capable of distinguishing various types of vehicles and classify them through AI and deep learning. The road analysis system developed by Folio3 makes use of surveillance cameras and specialized software to manage the cameras & visual data through intellectual analysis. It is also capable of interacting with other existing systems already being used for the purpose of traffic management.
Some key functionalities of our traffic analysis and management system are the capability of road supervision by observing the movement of traffic, capable of making fast decisions, and acting in real-time to call relevant authorities like police and ambulance in case of an accident or traffic violation.
It is also capable of monitoring traffic in real-time that is useful in taking actions proactively to save time in critical situations. It also enables centralized management for traffic control and management operations from the central office.
Our intelligent solution has proved to be a key element in saving lives and improve the situation of traffic for better and safer roads. We have used technologies like Yolo, SSD, and OpenCV in the development of this efficient solution.
Automated Authentication for Drive-Thrus
Our customer, named ‘Dashcode’, consulted us for the development of an intelligent solution for automation of the drive-thru process. We did substantial research to come up with a smart solution incorporating AI and image analytics to increase workflow efficiency and avoid the time-consuming drive-thru activities.
The manual process of drive-thru was time-consuming and had many choke-points that were responsible for the slow working of drive-thrus. We applied deep learning technology to change the working method of specific points in the drive-thru process to automate the processes and create a quality enterprise solution to ensure an enhanced drive-thru experience.
Our state-of-the-art product includes many highlights. Some of the significant features are discussed here. Automated authentication assists in confirming customer identity increase the pace of traffic through the line. A deep learning method helps the system to accurately identify the customers. Their vehicle’s make and model are also determined to enhance the ease in the identification process.
Our system performs automated transactions through analysis of live visuals. This helps in quick order-taking and avoiding the delay in transmissions to reduce time. Time efficiency is what keeps business running and customers satisfied. It also enables the system to process automated and secure payments in real-time. This, in turn, enables businesses to streamline order accuracy.
The technologies used in our drive-thru automation system includes TensorFlow, scikit-image. AM Turk, and various small tools and libraries.
Facial Recognition System
Our innovative approach urges us to develop solutions for complex challenges, and that’s why we have developed a highly accurate real-time facial recognition solution. Our system provides real-time results by using HOG (Histogram of Oriented Gradients) and Convolutional Neural Network (CNN). It also makes use of dLib for face recognition and object-oriented detection, our system is capable of accurately showcase results in real-time. The face recognition system offers a feasible option for biometric security. Another advantage of using face recognition is there is no need for making contact with a person who needs to be identified through the biometric process.
Some highlights of the face recognition system developed by Folio3 are discussed briefly here. Face searching enables the system to perform searches that would help in locating a specific person directly through the entries in the database by matching the specimen’s face.
Data management allows the system to share information with other systems by importing the JPEG format of generic photo data. It can be later used for face searching. Specific faces can be imported in advance to alert relevant authorities when the system observes them through surveillance cameras or any other source of visuals.
The system would automatically notify users through a pop up if it discovers the face of a specific person. It would also produce warning sounds and flashing the camera on the map. The system is handy in identifying the faces on its own and notify the users for proactive action. The technologies used in the development of this smart solution are CNN, HOG, DLIB, and OpenCV.
How Does Computer Vision Work FAQs
1) What is vision input system?
It incorporates the use of a computer vision system that acts as a sensor and delivers high-value information about what is around.
2) How does object tracking work in computer vision?
Object tracking tends to track objects as they move through a series of video frames. It is a fast-paced system in computer vision.
3) How does computer vision work in the new amazon go store?
Computer vision is used to implement the 3D vision that is used by Amazon technology in retail to monitor items without any need to scan barcodes.
Drawing the Line
AI has brought a revolution in human lifestyle and industrial processes. Computer vision is also a sub-section of AI. Computer vision is proving to be helpful in various industrial and retail processes. It also brings automation to processes that require manual operation otherwise. We hope that after reading this blog, you would get plenty of information about what is computer vision and how does computer vision works? Computer vision is used in many processes, which ultimately bring comfort to our everyday life and our living experience, all thanks to AI!
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