Computer vision is not a buzzword anymore. With AI (Artificial Intelligence) making rapid strides, computer vision has exceeded expectations in terms of what it is capable of. There is no domain that has not been ‘touched’ by computer vision and AI. Some of the modern-day smartphone cameras come integrated with computer vision capabilities, making it possible to perform tasks like low light imaging, accurate blurring, and adding various effects.
Though computer vision has been a late entrant to embedded vision, its impact has been significant. Embedded vision itself is in its early years and researchers are beginning to experiment with AI and computer vision in various embedded vision systems.
But what exactly is a computer vision camera? How does it help automate various tasks in industrial and commercial settings? What are the different embedded vision systems where they find application? Let’s explore all these in this blog post.
What is computer vision?
Let’s cover the basics first. Understanding computer vision is essential to learning what computer vision cameras are. Computer vision is nothing but the process of deriving insights from visual inputs such as images and videos. It helps machines and embedded devices convert visual data into a readable format for computers to take necessary actions.
Computer vision can be compared to the human eye while AI is like our brain. Eyes help us see. This data is then transmitted to the brain through optic nerves. The brain then interprets it and enables us to take action based on it. This is exactly how the combination of computer vision and AI works.
Computer vision with machine learning (or deep learning) leverages convolutional neural networks to make predictions based on what the device sees. The more the algorithm learns, the more accurate its analyses will be.
What is computer vision?
A computer vision camera is a camera system that uses algorithms to analyze and interpret what it sees. It is made possible by using specialized software that comes with the ability to perform various image analysis tasks.
For example, consider a smart surveillance system that can automatically detect theft and intrusions in secured areas like banks and military bases. It leverages computer vision cameras that can analyze image and video feeds to understand any unusual activity on the premises. Using the deep learning technique, they can learn over time and get better and more accurate at identifying unwanted objects or people.
When we say computer vision cameras, we typically refer to the complete camera system. Have a look at the below smart surveillance camera for example:

A smart surveillance camera
All such camera systems are made of embedded camera modules that come with the necessary features required for computer vision.
Take the same example of a smart surveillance system.
It should be capable of ensuring 24/7 security. This requires it to have the ability to capture sharp and clear images at night. This in turn means that the camera should have excellent low light sensitivity. In short, for a computer vision camera system to perform its intended tasks, the embedded camera module in it should meet certain quality standards. This is one of the strengths of TechNexion where we design, develop, and manufacture cameras that are perfectly suited for new-age computer vision and AI-based applications.
Working principle of computer vision cameras
A major part of integrating computer vision into camera systems involves training the model with the right set of data. Computer vision and deep learning algorithms are able to perform tasks like image recognition and classification since they are trained with datasets of images they are intended to analyze. For example, if a computer vision camera has to identify fruits and vegetables, the algorithm or model has to be trained with a diverse set of images that cover all possible types of fruits and vegetables.
We can compare this to how human intelligence works. Think about our whole lifecycle. When we are born, we have intelligence but don’t have any knowledge or context about the world. As we grow up, we learn and pick things up from the people around us. And we improve our cognitive abilities as we get older. This process is analogous to how computer vision models are trained. As they are fed with more data, they improve in accuracy and cognition.
Advantages of computer vision cameras
Clearly, computer vision cameras have been a game-changer across industries such as smart city, industrial automation, retail, and even healthcare. Some of their advantages include:
- They have helped automate various tasks which were once time consuming or dependent on human labor. An example of this is smart traffic management where lane violation can be automatically detected using computer vision cameras.
- They have resulted in significant cost reductions in the long run. Though the initial setup cost might be higher, computer vision cameras reduce cost over time in the form of reduced human labor, improved productivity, and increased safety.
- Computer vision cameras have given rise to newer use cases across industries. For example, remote patient monitoring systems of the past involved human personnel monitoring the patient. But today, computer vision and AI algorithms can automatically detect falls and send alerts to medical staff for immediate attention, all by just using cameras and no human involvement. AI-enabled medical diagnosis is another example.

Smart Traffic Management
- They have helped improve industrial and agricultural production. From product inspection to picking & placing and automated harvesting, computer vision has contributed to an increase in production capacity while achieving higher quality.
- Computer vision cameras have made more types of data available for advanced analytics. Earlier, visual data had to be analyzed manually, which had challenges when it came to standardization and scaling. With computer vision, image and video analysis can be done at scale.
Embedded vision applications of computer vision cameras
The use of computer vision in embedded vision has given rise to innovative applications that have made machines more efficient and intelligent. In this section, let us look at some of the most popular ones.
- Autonomous shopping
- Sports analytics and broadcasting
- Remote patient monitoring
- Robotics
Autonomous shopping
How do you think a completely automated shopping experience like Amazon Go is possible? It is by using AI and computer vision cameras. Whether it’s cameras at the checkout counter, shopping cart, roof, or retail shelves, cameras capture images and videos for computer vision algorithms to identify objects and track shopper activities. These camera systems are intelligent enough to identify different types of objects such as fruits & vegetables, packaged food, kitchen utensils, etc.
To learn more about how embedded vision is changing the way shopping is done using computer vision cameras and AI, check out the below article:
Embedded Vision in Autonomous Shopping – Transforming Shopping Experiences
Sports analytics and broadcasting
In the past, sports broadcasting was only done for professional matches. But embedded vision has changed that. By installing embedded cameras in sports arenas, amateur matches can be broadcast without even needing any personnel to operate the camera system. These cameras are usually mounted on poles in the field in a way that they can cover the entire area.
Computer vision has taken this to the next level by offering the ability to analyze the match visuals to derive key insights into player and team performance. By using techniques like ball tracking, computer vision cameras can analyze playing patterns, which is then used by coaches and team managers to come up with better game plans.
Learn more about sports analytics and broadcasting here: Embedded Vision in Sports Analytics – Relevance and Applications.
Remote patient monitoring
We touched upon this earlier. By leveraging computer vision and AI, patient monitoring can now be truly automated without the staff or caregivers having to give attention to the patient under observation throughout the day. Computer vision cameras today have become intelligent enough to detect patient movements, falls, and inactivity. In case of any suspicious event, an alert is automatically sent out to the staff for timely intervention.
Robotics

An industrial robot
Robotics is one of the applications of computer vision technology that has had a monumental impact on almost every industry. From enhancing warehouse operations and improving factory production to increasing agricultural output and delivering packages, robotics has found its way into various aspects of our lives.
Robots use computer vision cameras to identify objects, distinguish between them, and take actions based on it. For example, consider a delivery robot used to deliver packages and food. While autonomously navigating, it should be able to take extra safety measures when it sees a human vs. seeing a non-living thing. This means that the vision system in the robot should be intelligent enough to distinguish between humans and other objects. This is made possible using AI and computer vision.
More about how embedded vision is changing robotics here: Vision-guided Robotics – How Cameras are Transforming Robotics.
Other notable applications of computer vision cameras
The applications of computer vision cameras in embedded vision are endless. But here are a few more notable ones:
- Intelligent street lighting system
- Smart buses
- Skin scanning for medical diagnosis
- Industrial inspection
- Autonomous tractors
- Remote animal and bird watching
TechNexion – building embedded cameras that are computer vision-ready
TechNexion in the past few years has focused on building cameras that are suitable for modern day AI and computer vision applications such as robotics, smart traffic, autonomous shopping, and more. Our commitment to quality ensures that our cameras can capture images and videos that can be easily analyzed by computer vision algorithms. Learn more about our camera solutions here: Embedded vision cameras.
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- What is computer vision?
- What is computer vision?
- Working principle of computer vision cameras
- Advantages of computer vision cameras
- Embedded vision applications of computer vision cameras
- Other notable applications of computer vision cameras
- TechNexion â building embedded cameras that are computer vision-ready
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