3 research outputs found

    Detection of Automated Facial Beautification by a Camera Application by Comparing a Face to a Rearranged Face

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    This publication describes systems and techniques to detect if a camera application is applying an automated mechanism to beautify a human face present in a photograph. Some camera applications may automatically adjust characteristics of a face to “beautify” them, such as by changing a skin tone. Although provided as a feature, this “beautification” potentially can be interpreted as cultural insensitivity or can result in mental health concerns. Accordingly, enabling a user to at least have knowledge of automated beautification can be beneficial. Detecting beautification is accomplished by determining if a camera application adjusts pixels corresponding to a face but not pixels corresponding to a rearranged face. Facial recognition software recognizes the face but fails to recognize the rearranged face. A tile from the face is compared to a corresponding tile from the rearranged face. If the two tiles are sufficiently dissimilar, then the system infers that the camera application has adjusted the pixels of the tile corresponding to the original facial image responsive to recognizing those pixels as part of a face. In this manner, the automated facial beautification can be detected

    COMPATIBILITY TESTING FOR CAMERA APPLICATIONS TO FACILITATE SOFTWARE DEVELOPMENT

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    A system is described that provides a consistent application programming interface and enables compatibility testing for applications that interface with cameras across various mobile devices. The system includes one or more controlled testing environment modules that isolate mobile devices from ambient light and provide test charts and consistent internal lighting for camera testing. The controlled testing environment modules enable operating system developers to capture both landscape and portrait images, access features, and test applications in consistent testing environments across various mobile devices. Such testing may enable development of software shims to facilitate interaction with a wide variety of cameras across different vendors and implementations within individual mobile devices
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