Privacy-preserving camera captures only the objects you want

Over the past decade, digital cameras have become ubiquitous in modern life — embedded in smartphones, smart eyewear, security surveillance systems, autonomous vehicles and facial recognition technologies. And as the sheer amount of image data being captured has grown, so have concerns about privacy protection. In a paper recently published in the journal eLight, a team of researchers from the UCLA Samueli School of Engineering describe an artificial intelligence–informed smart camera that instantly captures only the objects of relevance in a frame while simultaneously blotting out unnecessary or potentially sensitive details, without the need for any editing, encryption or other digital post-processing work. Their device consists of several transmissive, 3D-printed surfaces (see image above), each composed of tens of thousands of diffractive features at the scale of the wavelength of light. The team used deep learning–based training to design and assemble the successive layers.

“We’d like to design a robust, power-efficient and secure smart camera that can safeguard privacy by controlling what a camera lens sees and captures before one clicks the shutter,” said lead researcher Aydogan Ozcan, the Volgenau Professor for Engineering Innovation at UCLA Engineering.

The research results are published in this article.

Read the full article at UCLA News.