Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they “see.”
Back in early 2011, Android 4 added a “geeky feature” that allowed you to unlock your phone with your face. But, the technology was so primitive and insecure, that even a picture of the person could unlock the phone. This tech took a backseat, and the fingerprint scanner drove the tech-scene for a long time.
With an estimated 16 million phones sold in just the first quarter of entering the market, the iPhone X was a sensation in 2017. Flaunting the revolutionary Face ID technology, the Apple device introduced a whole new era of mobile convenience. Face recognition technology in the device was so fine-tuned that it couldn’t even be fooled by identical twins. Currently, face unlock is a standard feature among all medium to premium segment smartphones.
This Face Recognition technology was possible with Computer Vision. Computer Vision is an aspect of Artificial Intelligence. It involves the extraction of data and information from visuals by computers.
1. What is Computer Vision?
If you come across the saying “a picture is worth a thousand words”, you probably know by now that the human brain extracts and analyses volumes of data using visual cues. Computer Vision is a rudimentary attempt at mimicking the biological function, of which we incidentally understand very little of. To understand how deeply rooted we are to the sense of sight, 40% of our nerve fibers are linked to the retina, and 90% of information transmitted to the brain is visual. Human brains can recognize patterns, shapes, colors, shades, contours, motion, and much more. We process visuals at 60,000X faster than text! To put it lightly, humans are visual creatures.
1.1 Computer Vision And Related Fields: What Makes CV Stand Out?
Computer vision is often clubbed with many other AI and ML fields that deal with aspects of visual learning. But, it’s important to understand that there are significant differences in each of the areas.
CV vs Image Processing
CV vs Machine Vision
1.2 What makes Computer Vision challenging?
While we have come a long way in the field of AI as a whole, the fact remains that the concept of deep learning is still yet to be explored to its full depth. What this essentially means is that computers are generally good at performing specific tasks in controlled environments. However, ComputerVision, in its real sense, is when computers can grasp clues from an open, unrestricted environment where the possibility of randomness and chaos is infinite. To do this has proven to be daunting at the least. What can aid deep learning is understanding how biological vision functions, and fitting those jigsaw puzzles into the AI system to make the computer “smarter”. Brain-eye coordination is a marvel of nature. Get to know about Computer Vision Application in real life by Downloading this Ebook
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