In recent years, the IT sector has rapidly advanced with the introduction of cutting-edge technological innovations. These advancements have driven the development of new AI applications, including conversational AI, generative AI, and visual AI. Among these, visual AI, also known as computer vision technology, has emerged as one of the most widely utilised applications of AI.
What is Computer Vision?
Computer Vision is a field of artificial intelligence (AI) that enables machines to interpret and understand the visual world. It involves the use of algorithms and models to process images and videos, allowing computers to recognise objects, faces, and even complex scenes. These systems equip machines with the ability to not only see but also process and respond to visual inputs in a meaningful and actionable manner. As technology advances, the importance of computer vision continues to grow, making it a cornerstone of modern visual intelligence. According to a report by Statista, the market size is expected to show an annual growth rate (CAGR 2024-2030) of 10.45%, resulting in a market volume of US$1.67bn by 2030.
Challenges in Computer Vision
Despite its introduction in 1960, computer vision still faces several challenges which include dealing with varying image quality, lighting conditions, and angles. These challenges can significantly affect the accuracy of recognition systems. The data required for training deep learning models also poses a challenge.
Ethical concerns, such as privacy issues and potential biases in AI algorithms, add another layer of complexity as reported by a report NITI Aayog in its report, ‘National Strategy for Artificial Intelligence #AIForAll’. Ensuring that computer vision systems are fair and unbiased requires careful consideration and rigorous testing.
Opportunities and Applications of Computer Vision
As an outcome of a resurgence of computer vision in 2010, numerous industries have begun implementing the technology to automate tasks, enhance accuracy, and reduce processing time. Several sectors have adopted this technology, including:
The integration of computer vision technology across sectors is reshaping mobility. In roadways and infrastructure, it is deployed for red light violation ticketing, accident alerts, smart parking, and license plate toll collection. Meanwhile, in aviation, it aids in both in-air and on-ground operations. On-ground, Visual AI cameras assist passengers with disabilities, detecting illegal objects, and enhancing efficiency during the boarding process and security check-in. For example, Adani Airport is utilising Visual AI technology to assist passengers with disabilities. The Visual AI cameras detect these passengers, enabling ground staff to provide necessary assistance.
When it comes to safety and security, facial recognition and anomaly detection systems fortify security in public and private areas, diminishing risks and fostering safety. Banking and finance sectors utilise computer vision to refine KYC processes, elevating customer financial security through transaction streamlining. This entails identity verification during transactions, ensuring heightened safety and efficiency.
In retail, it enhances inventory management, optimises store layouts, and provides deep customer insights via video analytics. Apart from the retail sector, the technology plays an instrumental role in the healthcare sector as well. It aids in early disease detection, particularly cancer, by analysing medical imaging such as X-rays and MRIs. This technology’s precision and efficiency transform operations and decision-making, promising improved customer experiences in retail and enhanced patient care in healthcare.
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These advancements signify a broader trend of leveraging technology to optimise safety, accessibility, and operations within critical sectors, promising a more connected and efficient future for the country.
Roadmap for Computer Vision
The future of computer vision is shaped by trends like edge computing, which reduces latency by processing data closer to the source, and AI advancements that enhance system capabilities with improved algorithms. The potential impact of computer vision technology spans various industries – in healthcare, it promises faster, more accurate diagnoses; in banking, it could streamline transactions for greater security; and in retail, it might revolutionise shopping with smart shelves and personalised recommendations.
The same report by NITI Aayog highlights that the adoption of AI globally is still in its nascent stages, but growing rapidly. However, as computer vision becomes more integrated into daily life, we can expect more sophisticated human-machine interfaces, increased accessibility, and new opportunities for innovation across sectors.
Conclusion
From revolutionising retail and healthcare to unlocking myriad possibilities yet unexplored, its impact is profound. As we harness its foundational principles and explore its vast applications, the horizon of a visually intelligent world beckons. Amidst challenges and opportunities, the journey toward this future is imminent. As we navigate the challenges and embrace the opportunities, the promise of a visually intelligent world is closer than ever.
