The Definition of Computer Vision

We live in a visual world, but we rarely think about the vast volumes of usable data within the photons that enter our eyes and are interpreted by our brains. Our ability to extract these visual signals was always limited by human capabilities – we simply cannot function as quickly and efficiently as a computer. AI, and subsequently Computer Vision (also known as Visual-AI), changed all that, allowing us to extract vast amounts of meaningful data from visual feeds in order to create key insights and make decisions that were previously impossible to imagine.

Computer Vision is a branch of Artificial Intelligence, and specifically Machine Learning that enables, not just hardware but also software to extract meaningful data from digital images and video. In the simplest of terms, Artificial Intelligence, in the broader sense, gives computers human-like ability to analyse and process data. However that data has to be delivered pre-formatted and annotated in order for AI to do its job. The challenge, therefore, is where the data is embedded, or ‘locked’ in images, video files or live video feeds. Computer Vision adds a vision system to the artificial brain, allowing it to see and process the world around it and therefore extract the data contained within, which can then be processed by the AI brain.

In real terms it’s not as simple as this. The human brain and vision system has had millions of years of evolution, which allows the human learning system to identify and differentiate between objects with one single exposure. Humans only need to see one example of a cat for us to be able to determine that any other example of the same thing is a cat, no matter the size, colour, breed, angle and even part of the cat we see. Computer Vision is still new by comparison and requires far more ‘learning’, i.e. exposure to hundreds of images of cats of different breeds, colours and poses, before it can achieve the same level of recognition accuracy.

However, this downside in learning is more than compensated by Computer Vision’s ability to process exponentially higher volumes of data than a human would be capable of. Where a human might be able to review hundreds of photos per day to detect and classify cats, Computer Vision could process hundreds of thousands.

More important is the difference in scalability. Attempting to process and detect cats in tens of millions of images per month would require an inconceivable number of human operators. Achieving the same using Computer Vision is simply a question of adding a few more CPU cores and more memory.

This processing efficiency is enabling new and wonderful technological breakthroughs from self-driving cars to cancer screening, and entirely new industries, such as brand monitoring and automated retail-shelf management.

A Diverse and Growing Technology

Computer vision is undoubtedly one of the most intriguing and compelling aspects of AI that many have perhaps even unknowingly experienced. 

Thanks to fast-moving advances in the field, and innovations in neural networks and deep learning, Visual-AI has come on leaps and bounds in the last five years and the application of the technology is almost boundless. This is in no small part due to the number of data humans generate on a daily basis, essentially gifting computer vision systems exactly what they need for their continued development and improvement. 

There is no doubt that while computer vision has developed at high speed, it has not yet reached its peak. It is applicable to an innumerable number of use cases and how it assists in these use cases continues to improve as computer vision, machine learning and neural networks continue to develop.

Why You Should Care About Computer Vision

Computer vision plays an important part in our lives, even if we don’t realise it, and that is why we should all care about and be thankful for it. 

Although there are some people who try their best to avoid introducing artificial intelligence into their day-to-day lives, it’s fair to say that there is no avoiding it. And while we understand that some aspects of computer vision, in particular, might be a little unsettling or appear invasive, we think it is a technological innovation that will ultimately continue to improve our lives. 

Computer vision can help reduce the risk of mental health difficulties in human content moderators. It can make production line managers’ lives a lot easier, from quality control enhancement to productivity analysis. Image recognition is already being used to detect cancer cells, which will be an incredible game changer when it becomes ubiquitous in the medical field. It’s also being used in dentistry. It has advanced herd management and crop monitoring. It makes our phones more secure and our streets and roads safer. 

Ultimately, the unknown aspects of computer vision are easily outweighed by the positives.

Computer Vision in Quality Control
Computer Vision in Quality Control
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Computer Vision in Dentistry
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Computer Vision in Road Safety

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