Computer vision, renewed with AI?
In the context of video, artificial intelligence (AI) refers to the ability of machines to mimic human behavior and, for example, perform tasks that require a deep understanding of visual information. As applications of artificial intelligence continue to develop, they are gradually influencing trends around video technologies, bringing efficiency and innovation.
How is the growing integration of artificial intelligence in video, with its image analysis and transformation capabilities, as well as its use in applications such as computer vision, transforming the visual industry?
Artificial intelligence (AI) enables in-depth analysis of images based on three key levels of visual analysis:
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Detection
That is, being able to distinguish an object from its background
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Acknowledgement
Recognition simply means that you are able to classify the object (is it a person or a car, a truck or a tank, etc.)
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Identification
It is the ability to describe the object in detail (a man with a tie, a Jeep, etc.)
Among the many visual AI models is FOMO, an acronym for “Faster Objects, More Objects”. This model focuses on detecting important visual information, providing real-time understanding of key elements in images. FOMO is a revolutionary algorithm that brings real-time object detection, tracking and counting for the first time. Visually, imagine a busy street with pedestrians, cars, and buildings coming and going. FOMO helps you monitor road safety and traffic by highlighting pedestrians crossing the road, traffic lights and other important features.
(Busy street)
YOLO, an acronym for “You Only Look Once” which translates into “you only look once”, meanwhile, it stands out for its ability to perform object detection in real time, providing results fast and accurate, making it a popular tool in many areas, from surveillance to security. Consider a scenario of monitoring a warehouse with pallets, forklifts and workers. YOLO will be able to accurately detect every pallet, every forklift and every worker on site in real time.
(Example of what YOLO can do: Identification using computer vision)
In addition to its analytical role, artificial intelligence is widely used to transform images using various filters and effects. Image editing apps use artificial intelligence algorithms to add artistic filters, adjust colors, improve clarity, and even generate photorealistic images from sketches or paintings.
(The AI that automatically retouches photos. Source: Siècle Digital)
We can take the DeepArt platform as an example. The platform uses machine learning algorithms to convert images into works of art in famous artistic styles. Users can upload their own images and transform them to imitate the styles of artists such as Van Gogh and Picasso.
(Source: DeepArt)
AI is a new tool that enhances the capabilities and functionalities of computer vision. Among these, facial recognition to unlock phones is one of the most widespread examples of integrating computer vision into daily life. This technology uses designated algorithms to identify and authenticate users' faces, thereby enhancing the security of mobile devices. You will find examples of capture creations on our page VERA – Nanopowered AI Camera.
There are different areas of application of computer vision. To begin with, we have physical retail for the analysis of footfall and customer behavior, the manufacturing industry for workplace safety and the detection of personal protective equipment, “intelligent” cities (or “smart cities”) for license plate recognition and traffic light optimization, as well as agriculture for livestock and crop monitoring.
In the industrial sector, computer vision is widely used for shape and part identification in manufacturing processes. For example, automated vision systems are able to recognize and sort different components or parts based on their specific shapes and characteristics, which significantly improves the efficiency of the production line.
(Control of the position of the part relative to the tool)
In medicine, computer vision is used for classification and analysis of medical images, such as x-rays and MRIs. With deterministic algorithms, healthcare professionals can make accurate diagnoses, detect abnormalities and diseases, and make informed medical decisions faster, significantly improving patient care and outcomes. Additionally, the healthcare industry is using computer vision for fall detection, posture recognition, social distancing monitoring, and fitness coaching.
(Computer vision improves healthcare)
The rise of artificial intelligence in video raises various ethical concerns, particularly regarding the loss of artistic authenticity due to the emergence of manipulated content such as fake videos and deepfakes. These technologies enable the creation of misleading visual content, jeopardizing the integrity of authentic media. For example, the ability to generate doctored videos of individuals giving speeches or committing acts they never did calls into question trust in the authenticity of visual information.
On the other hand, artificial intelligence is increasingly integrated into automated surveillance and video surveillance systems, raising fundamental questions regarding privacy and security. While these systems can help improve public safety, they also carry risks of privacy violations and intrusive surveillance. Additionally, the threat of hacking and manipulation of these systems by malicious actors raises concerns about data security and the protection of sensitive information.
The CNIL (national commission for information technology and freedoms) has issued an opinion on video surveillance with AI emphasizing the need to find a balance between the protection of individual rights and public security. In this opinion, the CNIL:
- highlights the uncertainty surrounding data protection and fundamental rights.
- underlines the need for legislative intervention to define acceptable limits by advocating a specific framework
- encourages the moderate use of these devices, with emphasis on a careful evaluation of their technical and operational performance
(CCTV camera)
The growing integration of artificial intelligence into video is radically changing the visual industry. Artificial intelligence is redefining the standards of creativity and efficiency across industries with its power of in-depth image analysis and artistic transformation. However, this development also raises ethical concerns and complex questions regarding data authenticity, privacy and security.
As the National Commission for Information Technology and Liberties points out, a balance must be found between technological innovation and protection of individual rights. As we continue to integrate artificial intelligence into video, it is essential to ensure that strong legal and ethical frameworks govern its use and maximize its benefits while minimizing the associated risks.
