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Computer Vision is a field of study that pursues to build practices to assist computers to see and comprehend the content of digital images like photographs and videos. It has been a subject of cumulative interest and rigorous research for decades now.
The market for computer vision is anticipated to rise from US$10.9 billion in 2019 to US$17.4 billion by 2024, at a growing CAGR of 7.8%, according to a report. The market is majorly driven by an increasing need for quality inspection and automation, mounting demand for vision-guided robotic systems and application-specific computer vision systems.
Computer vision is becoming more adroit at recognizing patterns from images than the human visual cognitive system. In the healthcare sector, for instance, computer vision-driven technologies have exceeded the pattern recognition capabilities of human physicians.
Lets, look at where the state of computer vision technology today and where it is in the future ahead.
The current state of computer vision technology is powered by deep learning algorithms that utilize a special kind of neural networks, Convolutional Neural Networks (CNNs), to make sense of images. These neural networks are trained to use thousands of sample images to assist the algorithm to comprehend and break down everything that is comprised of an image.
CNNs scan images pixel by pixel which recognizes patterns and memorizes them. These networks also memorize the ideal output that they should offer for each input image or categorizes components of images by scanning characteristics like contours and colors. Afterward, this memory is practiced by the systems as the reference while scanning more images, and with every iteration, the AI system becomes better at providing the precise output.
In several sectors computer vision technology is being used or tested, including healthcare – diagnosing diseases by assessing images received from CT scans and other medical procedures; Manufacturing – by leveraging this, manufacturers ensure manufacturing processes and finished products for non-conformance and imperfections; Security – using biometric analysis like retinal, facial recognition and fingerprint scanning to recognize individuals for security purposes.
Computer vision also is being leveraged in transportation to guide autonomous vehicles by detecting hurdles, people, and road signs along the way. As per the market research and insights, the automotive industry is one of the early adopters of computer vision systems and continues to lead the largest share of the computer vision market among other industries in the industrial vertical.
Since computer vision swells its impact in the human world, there are numerous things to contemplate on how it will alter the way people see their lives and how they live it. With additional research on and fine-tuning of the technology, the future of computer vision will see it perform a wide array of functions. The technology will not only be easier to train but also be able to discern more from images than they perform now.
Computer vision technologies will also be utilized alongside other technologies or other subsets of AI to create more compelling applications. Image captioning applications, for instance, where it can be integrated with natural language generation (NLG) to interpret the objects in the surroundings for visually challenged people. In the development of artificial general intelligence (AGI) and artificial superintelligence (ASI), computer vision also can portray a significant role by providing them the ability to process information or even better than the human visual system.
As a rising market, computer vision technology is firmly connected to visual and augmented reality (VR and AR). Indeed, the market players in recent time have a keen interest in the amalgamation of VR and AR. And such attention is growing at a rapid pace which is being reflected in the introduction of many state-of-the-art technological products.
