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 dynamic vision sensor (DVS) including a plurality of substrates electrically connected to one another and stacked vertically includes a photoelectric conversion device configured to generate charges in response to incident light from an external environment that is external to the DVS sensor, a bipolar junction transistor (BJT) device including a base connected to the photoelectric conversion device and configured to output a current based on amplifying a current output from the photoelectric conversion device, and a DVS pixel circuit that detects a change in intensity of the incident light and to output an event signal based on the current. The photoelectric conversion device is on a first substrate among the plurality of substrates. At least part of the DVS pixel circuit is on a different substrate from the first substrate among the plurality of substrates.

Abstract: A computing system for generating and displaying an encoded document for peripheral privacy is provided. The computing system includes a processor executing a program using portions of memory to determine an initial document, generate an encoded document based on the initial document by modifying letters in a text portion of the initial document, and output the encoded document. In another example, a computing system for displaying an encoded document for peripheral privacy is provided. The computing system includes a processor executing a program using portions of memory to receive an initial document and an encoded document, determine a gaze location of a user using a camera, generate a mask based on the determined gaze location, and display an alpha-blended document by alpha-blending the initial document and the encoded document using the mask.

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: 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: An eye tracking system for detecting position and movements of a user's eyes in a head-mounted display (HMD). The eye tracking system may include at least one near-IR (NIR) eye tracking camera positioned at each side of the user's face and pointed towards eye-facing surfaces of eyepieces of the HMD, an illumination source that emits NIR light towards the user's eyes, and hot mirrors located between the eye-facing surfaces of the eyepieces and the user's eyes. The hot mirrors reflect at least a portion of NIR light, while allowing visible light to pass. The cameras capture images of the user's eyes reflected by the hot mirrors. Positioning the hot mirrors at or near the eye-facing surfaces of the eyepieces allows the cameras to be placed at the sides of the user's face without having to image through the eyepieces.

Abstract: A wearable device includes a case, a bio-processor embedded in the case, and a plurality of electrodes connected to the bio-processor. The bio-processor is configured to selectively and respectively operate the electrodes as sensing electrodes and sourcing electrodes in response to a selection signal. The selected one/ones of the electrodes operated as sensing electrodes which pick up a biological signal from (e.g. biological activity or a biological condition of) the wearer. The selected one/ones of the electrodes operated as sourcing electrodes supply current to the wearer regulated to cause the desired biological signal to be picked up by the sensing electrode(s).

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: An electrode assembly for measuring bio-signals includes a body, a fastening member extending from the body and provided on one side of the body, the fastening member including a spring groove formed therein and an aperture penetrating therethrough, and a spring inserted into the spring groove. The aperture receives a fastening stud of a patch which is supplied from outside. The spring compresses the fastening stud received in the aperture such that the fastening member fixes the fastening stud thereto.

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: An apparatus for measuring bioelectrical signals is provided. The apparatus includes a sensor electrode, a sensor support, and a main body. The sensor electrode has a tapering portion that narrows toward one end and a protruding portion that extends from the one end of the tapering portion, contacts a body part, and senses bioelectrical signals. The sensor support maintains the contact between the sensor electrode and the body part. The main body is connected to the sensor support and is wearable on a living body.

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.

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 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: An apparatus is configured to perform a method for scrolling a display screen to correspond to a touch input in a mobile terminal. Upon detecting a touch input, the mobile terminal determines an actual coordinate value of the detected touch input, obtains a predicted coordinate value for the determined actual coordinate value, obtains a smoothed coordinate value by performing a smoothing operation on the obtained predicted coordinate value, and determines that the detected touch input has occurred at the obtained smoothed coordinate value.