Excited to introduce a new generation of privacy protecting smart cameras in our #ICCV2021 Oral paper by @CarlosH_93, @henarfu and myself 🇺🇸🇨🇴. See 🧵 below for details!
PDF: openaccess.thecvf.com/content/ICCV20…
Talk:
Project: carloshinojosa.me/project/privac…
@StanfordAILab
PDF: openaccess.thecvf.com/content/ICCV20…
Talk:
Project: carloshinojosa.me/project/privac…
@StanfordAILab
Our cameras introduce optical distortions at acquisition time, capturing images that protect the identity of people in the scene while enabling vision algorithms to perform inference accurately.
*Key idea*: joint end-to-end optimization of optical distortions & vision algorithm.
*Key idea*: joint end-to-end optimization of optical distortions & vision algorithm.
We achieve this by back-propagating all the way down to the camera lens. To make the lens shape differentiable, we parametrize it using Zernike polynomials.
Our system can be implemented in two ways. First, we can build a physical lens to enable hardware-level protection so that images are always distorted from the start, even at acquisition time. Note, this protection is orthogonal to other techniques such as differential privacy.
As a second option when attaching a new lens is not possible, we can implement our distortion in firmware/on-device, so that images are distorted immediately after acquisition but before the images leave the device, before they are stored or before any further processing.
For more details, see our #ICCV oral presentation during Session 2A and Session 2B. Looking forward to see you there!
Paper PDF: openaccess.thecvf.com/content/ICCV20…
Project: carloshinojosa.me/project/privac…
Talk:
Paper PDF: openaccess.thecvf.com/content/ICCV20…
Project: carloshinojosa.me/project/privac…
Talk:
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