Abstract: Lidar imaging techniques are disclosed. An example method includes projecting direct laser beams toward an area of interest, and projecting reflected laser beams toward the area of interest, wherein the reflected laser beams are reflected from a reflective surface disposed at a known location relative to an electronic device. The method also includes receiving light scattered in the area of interest due to the direct laser beams and the reflected laser beams. The method also includes determining signal characteristics of the detected scattered light received from the area of interest caused by both the direct laser beams and the reflected laser beams. The method also includes computing a depth map corresponding to the area of interest based on the signal characteristics.

Abstract: Examples of the disclosure relate to apparatus, methods and computer programs for calibrating machine learning systems by using images captured by an imaging device. The apparatus can comprise means for: enabling at least one of a first device or second device to display one or more calibration images, the first device comprising an embedded machine learning system wherein the one or more calibration images are for calibrating the embedded machine learning system. The apparatus can also comprise means for controlling an imaging device to capture, at least part of, the one or more calibration images, wherein the imaging device is provided within the first device, and using the one or more calibration images captured by the imaging device to calibrate the embedded machine learning system of the first device.

Abstract: An apparatus, method and computer program is disclosed. The apparatus may comprise means for receiving video data representing a video recording of at least one input made by a user at a user device; receiving audio data representing an audio recording of at least one audio input made by the user at the user device; determining whether there is a correspondence between the at least one input represented in the video data and the at least one audio input represented in the audio data; and providing verification based on the determination.

Abstract: Dust mitigation techniques are disclosed. An example apparatus includes a first component coupled in a movable relationship with a second component. The first component or the second component includes a recess accessible through an aperture. The apparatus also includes a brush disposed at the aperture and comprising fibers configured to prevent intrusion of dust into the recess. The apparatus also includes a vibration device configured to deliver a vibrational stimulus to the brush, wherein the vibration device activates a dust collection mode in response to a first movement of the first component relative to the second component and activates a dust shedding mode in response to a second movement of the first component relative to the second component.

Abstract: Examples of the disclosure relate to at least apparatus, methods, and computer programs, configured to control capture of two images of an area, across which a pulse propagates, using different shutter scanning directions. Either the images are converted into pulse-phase maps of the area and a pulse-phase difference map obtained which identifies differences between the pulse-phase maps of the area, or a colour difference map is obtained which identifies differences between the two images and the colour difference map is converted into a pulse-phase difference map. A shutter-time difference map is obtained which identifies differences between capture times of corresponding locations in the two images. Using the shutter-time difference map, the pulse-phase difference map is corrected to obtain a map of pulse-phase changes which have occurred over a duration of a shutter scan.

Abstract: A method, apparatus and computer program are described to determine a configuration of a reconfigurable screen of a user device, identify potentially problematic sources of reflection from a scene around a user device based, at least in part, on the determined configuration, and compensate for the potentially problematic sources of reflection.

Abstract: An apparatus, method and computer program is disclosed. The apparatus may comprise means for receiving video data representing a video recording of at least one input made by a user at a user device; receiving audio data representing an audio recording of at least one audio input made by the user at the user device; determining whether there is a correspondence between the at least one input represented in the video data and the at least one audio input represented in the audio data; and providing verification based on the determination.

Abstract: Dust mitigation techniques are disclosed. An example apparatus includes a first component coupled in a movable relationship with a second component. The first component or the second component includes a recess accessible through an aperture. The apparatus also includes a brush disposed at the aperture and comprising fibers configured to prevent intrusion of dust into the recess. The apparatus also includes a vibration device configured to deliver a vibrational stimulus to the brush, wherein the vibration device activates a dust collection mode in response to a first movement of the first component relative to the second component and activates a dust shedding mode in response to a second movement of the first component relative to the second component.

Abstract: Examples of the disclosure relate to at least apparatus, methods, and computer programs, configured to control capture of two images of an area, across which a pulse propagates, using different shutter scanning directions. Either the images are converted into pulse-phase maps of the area and a pulse-phase difference map obtained which identifies differences between the pulse-phase maps of the area, or a colour difference map is obtained which identifies differences between the two images and the colour difference map is converted into a pulse-phase difference map. A shutter-time difference map is obtained which identifies differences between capture times of corresponding locations in the two images. Using the shutter-time difference map, the pulse-phase difference map is corrected to obtain a map of pulse-phase changes which have occurred over a duration of a shutter scan.

Abstract: Examples of the disclosure relate to an apparatus for enabling LiDAR measurements. The apparatus comprises means for detecting relative movement between at least one object and at least one LiDAR device wherein the at least one LiDAR device is configured to provide a measurement location projection pattern. The apparatus also comprises means for predicting a location of at least one area of interest of the at least one object relative to the at least one LiDAR device at a given time and adding a delay to transmission of the measurement location projection pattern. The delay is added so that one or more measurement locations of the measurement location projection pattern are incident on the at least one area of interest of the at least one object at the given time.

Abstract: Examples of the disclosure relate to apparatus, methods and computer programs for calibrating machine learning systems by using images captured by an imaging device. The apparatus can comprise means for: enabling at least one of a first device or second device to display one or more calibration images, the first device comprising an embedded machine learning system wherein the one or more calibration images are for calibrating the embedded machine learning system. The apparatus can also comprise means for controlling an imaging device to capture, at least part of, the one or more calibration images, wherein the imaging device is provided within the first device, and using the one or more calibration images captured by the imaging device to calibrate the embedded machine learning system of the first device.

Abstract: A method, apparatus and computer program is described comprising: determining a configuration of a reconfigurable screen of a user device; identifying potentially problematic sources of reflection from a scene around a user device based, at least in part, on the determined configuration; and compensating for said potentially problematic sources of reflection.

Abstract: Lidar imaging techniques are disclosed. An example method includes projecting direct laser beams toward an area of interest, and projecting reflected laser beams toward the area of interest, wherein the reflected laser beams are reflected from a reflective surface disposed at a known location relative to an electronic device. The method also includes receiving light scattered in the area of interest due to the direct laser beams and the reflected laser beams. The method also includes determining signal characteristics of the detected scattered light received from the area of interest caused by both the direct laser beams and the reflected laser beams. The method also includes computing a depth map corresponding to the area of interest based on the signal characteristics.