  As cameras become ubiquitous in our living environment, invasion of privacy
is becoming a growing concern. A common approach to privacy preservation is to
remove personally identifiable information from a captured image, but there is
a risk of the original image being leaked. In this paper, we propose a
pre-capture privacy-aware imaging method that captures images from which the
details of a pre-specified anonymized target have been eliminated. The proposed
method applies a single-pixel imaging framework in which we introduce a
feedback mechanism called an aperture pattern generator. The introduced
aperture pattern generator adaptively outputs the next aperture pattern to
avoid sampling the anonymized target by exploiting the data already acquired as
a clue. Furthermore, the anonymized target can be set to any object without
changing hardware. Except for detailed features which have been removed from
the anonymized target, the captured images are of comparable quality to those
captured by a general camera and can be used for various computer vision
applications. In our work, we target faces and license plates and
experimentally show that the proposed method can capture clear images in which
detailed features of the anonymized target are eliminated to achieve both
privacy and utility.
