Abstract: Gaze is corrected by adjusting multi-view images of a head. Image patches containing the left and right eyes of the head are identified and a feature vector is derived from plural local image descriptors of the image patch in at least one image of the multi-view images. A displacement vector field representing a transformation of an image patch is derived, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector produced by machine learning. The multi-view images are adjusted by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

Abstract: Methods and devices for generating reference data for adjusting a digital representation of a head region, and methods and devices for adjusting the digital representation of a head region are disclosed. In some arrangements, training data are received. A first machine learning algorithm generates first reference data using the training data. A second machine learning algorithm generates second reference data using the same training data and the first reference data generated by the first machine learning algorithm.

Abstract: Generating data to provide an animated visual representation is disclosed. A method comprises receiving input data obtained by a first sensor system measuring information about at least one target person. One data unit is selected from a database comprising a plurality of the data units. Each data unit comprises information about a reference person in a reference state measured at a previous time by the first sensor system or by a second sensor system. The information in each data unit allows generation of an animated visual representation of the reference person in the reference state. The reference state is different for each of the data units. The selected data unit and the input data are used to generate output data usable to provide an animated visual representation corresponding to the target person and synchronized with activity of the target person measured by the first sensor system.

Abstract: A computing system, a method, and a computer-readable storage medium for adjusting eye gaze are described. The method includes capturing a video stream including images of a user, detecting the user's face region within the images, and detecting the user's facial feature regions within the images based on the detected face region. The method includes determining whether the user is completely disengaged from the computing system and, if the user is not completely disengaged, detecting the user's eye region within the images based on the detected facial feature regions. The method also includes computing the user's desired eye gaze direction based on the detected eye region, generating gaze-adjusted images based on the desired eye gaze direction, wherein the gaze-adjusted images include a saccadic eye movement, a micro-saccadic eye movement, and/or a vergence eye movement, and replacing the images within the video stream with the gaze-adjusted images.

Abstract: Gaze is corrected by adjusting multi-view images of a head. Image patches containing the left and right eyes of the head are identified and a feature vector is derived from plural local image descriptors of the image patch in at least one image of the multi-view images. A displacement vector field representing a transformation of an image patch is derived, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector produced by machine learning. The multi-view images are adjusted by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

Abstract: Methods and devices for generating reference data for adjusting a digital representation of a head region, and methods and devices for adjusting the digital representation of a head region are disclosed. In some arrangements, training data are received. A first machine learning algorithm generates first reference data using the training data. A second machine learning algorithm generates second reference data using the same training data and the first reference data generated by the first machine learning algorithm.

Abstract: A computing system, a method, and a computer-readable storage medium for adjusting eye gaze are described. The method includes capturing a video stream including images of a user, detecting the user's face region within the images, and detecting the user's facial feature regions within the images based on the detected face region. The method includes determining whether the user is completely disengaged from the computing system and, if the user is not completely disengaged, detecting the user's eye region within the images based on the detected facial feature regions. The method also includes computing the user's desired eye gaze direction based on the detected eye region, generating gaze-adjusted images based on the desired eye gaze direction, wherein the gaze-adjusted images include a saccadic eye movement, a micro-saccadic eye movement, and/or a vergence eye movement, and replacing the images within the video stream with the gaze-adjusted images.

Abstract: Gaze is corrected by adjusting multi-view images of a head. Image patches containing the left and right eyes of the head are identified and a feature vector is derived from plural local image descriptors of the image patch in at least one image of the multi-view images. A displacement vector field representing a transformation of an image patch is derived, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector produced by machine learning. The multi-view images are adjusted by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

Abstract: Generating data to provide an animated visual representation is disclosed. A method comprises receiving input data obtained by a first sensor system measuring information about at least one target person. One data unit is selected from a database comprising a plurality of the data units. Each data unit comprises information about a reference person in a reference state measured at a previous time by the first sensor system or by a second sensor system. The information in each data unit allows generation of an animated visual representation of the reference person in the reference state. The reference state is different for each of the data units. The selected data unit and the input data are used to generate output data usable to provide an animated visual representation corresponding to the target person and synchronized with activity of the target person measured by the first sensor system.

Abstract: Methods and devices for generating reference data for adjusting a digital representation of a head region, and methods and devices for adjusting the digital representation of a head region are disclosed. In some arrangements, training data are received. A first machine learning algorithm generates first reference data using the training data. A second machine learning algorithm generates second reference data using the same training data and the first reference data generated by the first machine learning algorithm.

Abstract: A directional display apparatus including a directional display device that is capable of directing a displayed image into a viewing window of variable width is provided with a privacy control function. A control system detects the presence of one or more secondary viewers in addition to a primary viewer, and decides whether the one or more secondary viewers is permitted to view the displayed image. The control system directs a displayed image into a viewing window which is adjusted, for example by decreasing the width, in dependence on that detection. In addition, the control system detects relative movement between the primary viewer and the display device, and the width of the viewing window is increased in response to detection of said relative movement.

Abstract: Generating data to provide an animated visual representation is disclosed. A method comprises receiving input data obtained by a first sensor system measuring information about at least one target person. One data unit is selected from a database comprising a plurality of the data units. Each data unit comprises information about a reference person in a reference state measured at a previous time by the first sensor system or by a second sensor system. The information in each data unit allows generation of an animated visual representation of the reference person in the reference state. The reference state is different for each of the data units. The selected data unit and the input data are used to generate output data usable to provide an animated visual representation corresponding to the target person and synchronized with activity of the target person measured by the first sensor system.

Abstract: A method includes generating calibration data by geometrically calibrating first image data from a first camera unit relative to second image data from a second camera unit based on first descriptor data and second descriptor data. The first descriptor data is based on the first image data. The second descriptor data is based on the second image data. The calibration data is generated based on first position data corresponding to the first camera unit and second position data corresponding to the second camera unit. The method includes identifying, based on the calibration data, a target location relative to the first image data. The method further includes generating an output image that includes the first image data and an indication of where the target location is relative to a scene depicted in the first image data.

Abstract: Gaze is corrected by adjusting multi-view images of a head. Image patches containing the left and right eyes of the head are identified and a feature vector is derived from plural local image descriptors of the image patch in at least one image of the multi-view images. A displacement vector field representing a transformation of an image patch is derived, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector produced by machine learning. The multi-view images are adjusted by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

Abstract: Methods and devices for generating reference data for adjusting a digital representation of a head region, and methods and devices for adjusting the digital representation of a head region are disclosed. In some arrangements, training data are received. A first machine learning algorithm generates first reference data using the training data. A second machine learning algorithm generates second reference data using the same training data and the first reference data generated by the first machine learning algorithm.

Abstract: Gaze is corrected by adjusting multi-view images of a head. Image patches containing the left and right eyes of the head are identified and a feature vector is derived from plural local image descriptors of the image patch in at least one image of the multi-view images. A displacement vector field representing a transformation of an image patch is derived, using the derived feature vector to look up reference data comprising reference displacement vector fields associated with possible values of the feature vector produced by machine learning. The multi-view images are adjusted by transforming the image patches containing the left and right eyes of the head in accordance with the derived displacement vector field.

Abstract: Methods and devices for generating reference data for adjusting a digital representation of a head region, and methods and devices for adjusting the digital representation of a head region are disclosed. In some arrangements, training data are received. A first machine learning algorithm generates first reference data using the training data. A second machine learning algorithm generates second reference data using the same training data and the first reference data generated by the first machine learning algorithm.

Abstract: An imaging directional backlight apparatus including a waveguide, a light source array, for providing large area directed illumination from localized light sources. The waveguide may include a stepped structure, in which the steps may further include extraction features optically hidden to guided light, propagating in a first forward direction. Returning light propagating in a second backward direction may be refracted, diffracted, or reflected by the features to provide discrete illumination beams exiting from the top surface of the waveguide. Viewing windows are formed through imaging individual light sources and hence defines the relative positions of system elements and ray paths. Lateral non-uniformities of output image are improved by means of adjustment of input aperture shape and reflective aperture shape. Cross talk in autostereoscopic and privacy displays may further be improved by light blocking layers arranged on the input end of the waveguide.

Abstract: A directional display apparatus including a directional display device that is capable of directing a displayed image into a viewing window of variable width is provided with a privacy control function. A control system detects the presence of one or more secondary viewers in addition to a primary viewer, and decides whether the one or more secondary viewers is permitted to view the displayed image. The control system directs a displayed image into a viewing window which is adjusted, for example by decreasing the width, in dependence on that detection. In addition, the control system detects relative movement between the primary viewer and the display device, and the width of the viewing window is increased in response to detection of said relative movement.

Abstract: A method includes generating calibration data by geometrically calibrating first image data from a first camera unit relative to second image data from a second camera unit based on first descriptor data and second descriptor data. The first descriptor data is based on the first image data. The second descriptor data is based on the second image data. The calibration data is generated based on first position data corresponding to the first camera unit and second position data corresponding to the second camera unit. The method includes identifying, based on the calibration data, a target location relative to the first image data. The method further includes generating an output image that includes the first image data and an indication of where the target location is relative to a scene depicted in the first image data.