Abstract: Examples are disclosed that relate to the restoration of degraded images acquired via a behind-display camera. One example provides a method of training a machine learning model, the method comprising inputting training image pairs into the machine learning model, each training image pair comprising an undegraded image and a degraded image that represents an appearance of the undegraded image to a behind-display camera, and training the machine learning model using the training image pairs to generate frequency information that is missing from the degraded images.

Abstract: A computing device is disclosed that includes an organic light-emitting diode (OLED) display. The OLED display has a front surface and a back surface. The computing device includes a moveable display support connected to the back surface of the display. In some implementations, the moveable display support is configured to limit bending in one direction to a first bend radius and to limit bending in another direction to a second bend radius. In some implementations, the moveable display support is formed by a plurality of unit cells.

Abstract: Examples are disclosed that relate to the restoration of degraded images acquired via a behind-display camera. One example provides a method of training a machine learning model, the method comprising inputting training image pairs into the machine learning model, each training image pair comprising an undegraded image and a degraded image that represents an appearance of the undegraded image to a behind-display camera, and training the machine learning model using the training image pairs to generate frequency information that is missing from the degraded images.

Abstract: Examples are disclosed herein that relate to determining whether an imaged subject is real or spoofed. One example provides a computing system, comprising, a camera, a light pattern source configured to output a light pattern, a logic subsystem, a storage subsystem storing instructions executable by the logic subsystem to capture, via the camera, an image of a subject illuminated by the light pattern emitted by the light pattern source, determine, based at least upon a contrast of the light pattern in the image, whether the subject is real or a spoof, based at least upon determining that the subject is real, perform an action on the computing system, and based at least up on determining that the subject is a spoof, not perform the action on the computing system.

Abstract: A computing device is disclosed that includes an organic light-emitting diode (OLED) display. The OLED display has a front surface and a back surface. The computing device includes a moveable display support connected to the back surface of the display. In some implementations, the moveable display support is configured to limit bending in one direction to a first bend radius and to limit bending in another direction to a second bend radius. In some implementations, the moveable display support is formed by a plurality of unit cells.

Abstract: A computing device is disclosed that includes an organic light-emitting diode (OLED) display. The OLED display has a front surface and a back surface. The computing device includes a moveable display support connected to the back surface of the display. In some implementations, the moveable display support is configured to limit bending in one direction to a first bend radius and to limit bending in another direction to a second bend radius. In some implementations, the moveable display support is formed by a plurality of unit cells.

Abstract: An electronic device comprises a display, an illumination source, a camera, and a logic system. The illumination source is configured to project structured illumination onto a subject. The camera is configured to image the subject through the display, which includes collecting the structured illumination as reflected by the subject. The logic system is configured to receive, from the camera, a digital image of the subject imaged through the display. The logic system is further configured to sharpen the digital image based on the spatially resolved intensity of the structured illumination as reflected by the subject.

Abstract: Examples are disclosed that relate to the restoration of degraded images acquired via a behind-display camera. One example provides a method of training a machine learning model, the method comprising inputting training image pairs into the machine learning model, each training image pair comprising an undegraded image and a degraded image that represents an appearance of the undegraded image to a behind-display camera, and training the machine learning model using the training image pairs to generate frequency information that is missing from the degraded images.

Abstract: Examples are disclosed that relate to the restoration of degraded images acquired via a behind-display camera. One example provides a method of training a machine learning model, the method comprising inputting training image pairs into the machine learning model, each training image pair comprising an undegraded image and a degraded image that represents an appearance of the undegraded image to a behind-display camera, and training the machine learning model using the training image pairs to generate frequency information that is missing from the degraded images.

Abstract: Examples are disclosed that relate to the restoration of degraded images acquired via a behind-display camera. One example provides a method of training a machine learning model, the method comprising inputting training image pairs into the machine learning model, each training image pair comprising an undegraded image and a degraded image that represents an appearance of the undegraded image to a behind-display camera, and training the machine learning model using the training image pairs to generate frequency information that is missing from the degraded images.

Abstract: Embodiments enable forming a friction modified touch sensitive surface on a touch screen panel. In particular, the touch sensitive surface is augmented with two friction modifying materials that are interspersed with one another according to a predetermined pattern on the surface of the touch screen panel as a monomolecular layer. In an embodiment, The materials have indices of refraction that differ from each other by more than 0.10. In another embodiment, the materials have a kinetic coefficient of friction in one or the other range, respectively, of between 0.01 and 0.05, or between 0.06 and 0.1, said kinetic coefficients of friction being measured against printing paper that has a kinetic coefficient of friction of 0.17 with itself. In another embodiment, the materials have a water contact angle of greater than 90 degrees, and an oil contact angle of greater than 30 degrees as measured with n-hexadecane.

Abstract: A computing device is disclosed that includes an organic light-emitting diode (OLED) display. The OLED display has a front surface and a back surface. The computing device includes a moveable display support connected to the back surface of the display. In some implementations, the moveable display support is configured to limit bending in one direction to a first bend radius and to limit bending in another direction to a second bend radius. In some implementations, the moveable display support is formed by a plurality of unit cells.

Abstract: A computing device is disclosed that includes an organic light-emitting diode (OLED) display. The OLED display has a front surface and a back surface. The computing device includes a moveable display support connected to the back surface of the display. In some implementations, the moveable display support is configured to limit bending in one direction to a first bend radius and to limit bending in another direction to a second bend radius. In some implementations, the moveable display support is formed by a plurality of unit cells.

Abstract: An electronic device includes a cover glass having a display surface, a pixelated photoemitting element array, and a pixelated photodetecting element array. The pixelated photoemitting element array emits a light signal through the cover glass to the display surface. The pixelated photodetecting element array is positioned relative to the pixelated photoemitting element array and the cover glass to receive a reflected light signal. The reflected light signal includes a portion of the emitted light signal reflected by total internal reflection from a refractive boundary at the display surface. Operation of each pixel is switched between the one or more photodetecting elements and the one or more photoemitting elements by the pixel selector signal component received from the pixel selector signal bus. A sensing trigger is configured to trigger the imaging scan by the pixelated photoemitting element array and the pixelated photodetecting element array, responsive to detection of an initiating action.

Abstract: An electronic device includes a cover glass having a display surface, a pixelated photoemitting element array, and a pixelated photodetecting element array. The pixelated photoemitting element array emits a light signal through the cover glass to the display surface. The pixelated photodetecting element array is positioned relative to the pixelated photoemitting element array and the cover glass to receive a reflected light signal. The reflected light signal includes a portion of the emitted light signal reflected by total internal reflection from a refractive boundary at the display surface. Operation of each pixel is switched between the one or more photodetecting elements and the one or more photoemitting elements by the pixel selector signal component received from the pixel selector signal bus. A sensing trigger is configured to trigger the imaging scan by the pixelated photoemitting element array and the pixelated photodetecting element array, responsive to detection of an initiating action.

Abstract: Systems and methods for foreground image segmentation, which receive image data captured at a first time, generate a skeleton model of a foreground subject captured in the image data, generate an initial foreground mask for a foreground segment including the foreground subject, generate secondary points corresponding to the foreground subject, identify supplemental points for the foreground segment based on at least the secondary points and the skeleton model, combine the supplemental points with the initial foreground mask to obtain a combined mask, obtain a foreground segment mask for the foreground subject based on the combined mask, and apply the foreground segment mask to the image data to obtain a foreground image portion for the foreground subject.

Abstract: Techniques for video capture including determining a position of a subject in relation to multiple cameras; selecting a foreground camera from the cameras based on at least the determined position; obtaining an RGB image captured by the foreground camera; segmenting the RGB image to identify a foreground portion corresponding to the subject, with a total height of the foreground portion being a first percentage of a total height of the RGB image; generating a foreground image from the foreground portion; producing a composite image, including compositing the foreground image and a background image to produce a portion of the composite image, with a total height of the foreground image in the composite image being a second percentage of a total height of the composite image and the second percentage being substantially less than the first percentage; and causing the composite image to be displayed on a remote system.

Abstract: Techniques for video conferencing including obtaining a first image captured by a camera through a display device of a first device, receiving at the first device live images of a first participant of a video conferencing session, displaying a first composite image on the display device with an image portion of the eyes of the first participant at a lateral position corresponding to the camera, segmenting a foreground image from the first image that corresponds to a second participant of the video conferencing session, and causing via the video conferencing session a second composite image of the second device at a different geographic location, in which the second composite image includes the foreground image composited with a background image.

Abstract: Techniques for video conferencing including obtaining a first image captured by a camera through a display device of a first device, receiving at the first device live images of a first participant of a video conferencing session, displaying a first composite image on the display device with an image portion of the eyes of the first participant at a lateral position corresponding to the camera, segmenting a foreground image from the first image that corresponds to a second participant of the video conferencing session, and causing via the video conferencing session a second composite image of the second device at a different geographic location, in which the second composite image includes the foreground image composited with a background image.

Abstract: Systems and methods for foreground image segmentation, which receive image data captured at a first time, generate a skeleton model of a foreground subject captured in the image data, generate an initial foreground mask for a foreground segment including the foreground subject, generate secondary points corresponding to the foreground subject, identify supplemental points for the foreground segment based on at least the secondary points and the skeleton model, combine the supplemental points with the initial foreground mask to obtain a combined mask, obtain a foreground segment mask for the foreground subject based on the combined mask, and apply the foreground segment mask to the image data to obtain a foreground image portion for the foreground subject.