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Scientists have created a compact camera with innovative optics, accelerating object identification with greater speed and energy efficiency
Scientists from two of the United States' leading universities, Washington University and Princeton University, have developed a revolutionary compact panoramic camera for computer vision.
Using an innovative approach, the new prototype reduces energy consumption the energy and promises to identify objects at an impressive speed: the speed of light.
Computer vision with a new camera
Computer vision is an area of artificial intelligence that allows computers to reflect and interpret images and videos.
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Traditionally, computer vision systems rely on electronic processing done by conventional hardware. However, researchers have found a way to perform some of this reporting directly in the camera optics.
Arka Majumdar, professor of electrical engineering and physics at the University of Washington, explains the innovation: “This is a completely new way of thinking about optics, very different from the traditional way. The optics are designed together with the computational block, allowing the transmission to be performed optically.. "
Instead of using a conventional glass or plastic lens, the new one uses layers of 50 metal-lenses, which are lightweight, flat lenses composed of microscopic nanostructures.
These structures manipulate light and function as an optical neural network, an AI system inspired by the functioning of the human brain.
Practical advantages and energy efficiency
One of the main advantages of this approach is speed. The camera operates with the publication performed at the speed of light, allowing it to identify and classify images more than 200 times faster than traditional neural networks, which use conventional hardware.
And it's not just the speed that's impressive, the precision is achieved using the most advanced neural networks. In addition, energy consumption is significantly reduced, as the camera's optics use incoming light to operate, unlike traditional systems that rely on electricity.
Felix Heide, a professor at Princeton University, highlights the broad potential of this research. He mentions that applications could range from self-driving cars to medical devices and smartphones.
"Today, every iPhone has AI or vision technology. This work is still in its early stages, but it could benefit these devices in the future."
The impact on the development of autonomous vehicles
The study, published in the journal Science Advances, presents a significant advance in optical computing.
By integrating this technology with the camera's optics, researchers have developed a computer vision system capable of performing neural network calculations during image capture, even before recording them on the camera's sensor. This enables real-time analysis with impressive precision.
Scientists are also looking to the future, with the technology expected to play a key role in navigating autonomous vehicles.
As part of the next stage of research, they plan to test the prototype on more complex datasets and on problems that unlock greater computational power, such as object detection.
This type of technology is essential for autonomous cars to be able to identify obstacles and make decisions in real time.
