Abstract: Aspects of the present disclosure relate to a computer-implemented method of processing data portion. The method comprises processing a first data portion in a convolutional neural network to generate a first input to an activation function in the convolutional neural network; providing a first output by applying the activation function to the first input; and storing an indicator, representative of the first input to the activation function, for the first data portion. The method further comprises determining whether to provide a second output by applying the activation function to a second input, generated from a second data portion, based at least in part on an evaluation of the indicator for the first data portion.

Abstract: A human-machine interface system comprises a sensor configured to generate data associated with a human movement, such as measured electrical signals or data from an accelerometer. A measurement unit of the human-machine interface measures user movement over time to generate a sequence of measured user movement data. A processor processes the data associated with a human movement from the sensor using a trained neural network to determine one or more predicted user actions. A comparison unit compares the one or more predicted user actions with one or more user actions obtained from the sequence of measured user movement data. A control unit uses the predicted user actions to control a process in an information processing apparatus in dependence upon the comparison performed by the comparison unit.

Abstract: A head-mounted display (HMD) comprising a first side for facing a user of the HMD, a second side opposite to the first side, and a reflective layer for at least partially reflecting incident light incident on the second side. At least one processor of the HMD is configured to obtain luminance data indicative of a luminance of the incident light and control a display device, based on the luminance data, to control a luminance of a portion of emitted light directed towards the user of the HMD during the display of the image. Further examples relate to an HMD with a display device configured to emit light of at least one predetermined wavelength range during display of an image by the display device, and a layer arranged to at least partially prevent transmission of the light of the at least one predetermined wavelength range outward from the HMD.

Abstract: Disclosed subject matter relates generally to predictive graphics processing for interactive content.

Abstract: A human-machine interface system comprises a sensor configured to generate data associated with a human movement, such as measured electrical signals or data from an accelerometer. A measurement unit of the human-machine interface measures user movement over time to generate a sequence of measured user movement data. A processor processes the data associated with a human movement from the sensor using a trained neural network to determine one or more predicted user actions. A comparison unit compares the one or more predicted user actions with one or more user actions obtained from the sequence of measured user movement data. A control unit uses the predicted user actions to control a process in an information processing apparatus in dependence upon the comparison performed by the comparison unit.

Abstract: An AR system is provided, the AR system including one or more sensors, storage, one or more communications modules, and one or more processors. The one or more sensors generate sensed data representing at least part of an environment in which the AR system is located. The one or more communications modules transmit localization data to be used in determining the location and orientation of the AR system. The one or more processors are arranged to obtain sensed data representing an environment in which the AR system is located, process the sensed data to identify a first portion of the sensed data which represents redundant information, derive localization data, wherein the localization data is derived from the sensed data and the first portion is obscured during the derivation of the localization data, and transmit at least a portion of the localization data using the one or more communication modules.

Abstract: A computer implemented method for performing convolutions between subsets of an input data array and a kernel resulting in subsets of an output data array. The method may include receiving an input data array and using positional data indicating the position of elements of the input data array to determine subsets of the input data array which contains at least one non-zero value data element; performing convolutions between the subsets of the input data array containing at least one non-zero value data element and a kernel to produce output data array subsets; and combining the output data subsets with the positional data to generate output data indicative of a completed output data array.

Abstract: A local object classifier using a set of object definitions to perform object classification in image frames. The local object classifier is arranged to detect an object in an image frame and determine whether to transmit image data for the detected object to a remote object classifier. In response to said determining, the local object classifier is arranged to transmit image data, derived from the image data representative of the image frame, to the remote object classifier. The local object classifier is also arranged to receive object data, representative of the detected object, from the remote object classifier.

Abstract: An image processing system for an extended reality, XR, device comprising an eye-tracking subsystem, for determining a focus region of the eye, and a processor. The processor is configured to process application data to render image content for an application for display on the XR device, and obtain metadata indicating that a virtual object is to be generated as a hologram as part of the image content for display. Based on a determination that the virtual object belongs to a predetermined class of objects and is to be displayed in the focus region, the processor performs, using a neural network corresponding to the predetermined class of objects, foveated processing of the image content, including at least part of the hologram, such that relatively high-quality image content is generated for display in the focus region and relatively low-quality image content is generated for display outside the focus region.

Abstract: The present disclosure relates to a method of operating a graphics processing system for providing frames over communication channel in a communication network, the graphics processing system being configured to process data for an application executed thereon to render frames for the application to be output for transmission over the communication channel to a client device, the method comprising: determining network characteristics of the communication network and/or server characteristics of the server; adaptively selecting a first prediction method from a plurality of prediction methods to be used for displaying frames based on the determined network characteristics and/or server characteristics; generating a plurality of frames based on the first prediction method; and selectively providing, based on the first prediction method, one or more output frames from the plurality of frames to the application to be output for transmission over the communication channel.

Abstract: A method of controlling an imaging system for a Head Mounted Display (HMD) device. The method comprises capturing an external scene, for example using a camera, determining an attenuation pattern, for rendering a filter area. The method also comprises determining, based on the captured external scene, a compensation pattern to for compensating at least part of the filter area, attenuating the external scene using the attenuation pattern and generating a holographic image of a virtual object, the holographic image including the compensation pattern.

Abstract: A system for estimating a current camera pose corresponding to a current point in time using a previous camera pose corresponding to a previous point in time, of a camera configured to generate a sequence of image frames. The system performs operations, including: generating, using one or more neural networks, a neural network pose prediction for the current image frame; and adjusting a previous camera pose using inertial measurement unit data representing a motion of the camera between the previous point in time and the current point in time, to provide an inertial measurement unit pose prediction for the current point in time. The inertial measurement unit pose prediction, and the neural network pose prediction are combined in order to estimate the current camera pose.

Abstract: An AR system includes one or more image sensors arranged to capture image data representing a scene located within a field of view of the one or more image sensors, a display arranged to enable a user of the AR system to observe a representation or view of the scene, and an augmentation engine. The augmentation engine is arranged to process the captured image data to determine one or more visual characteristics for the captured image data and to determine, in dependence on the determined one or more visual characteristics, one or more properties for an image element to be presented on the display. The augmentation engine is arranged to present the image element, with the determined one or more properties, on the display to overlay the representation or view of the scene.

Abstract: A graphics processing system and method of operating a graphics processing system that generates “spacewarped” frames for display is disclosed. Motion vectors are used to determine the motion of objects appearing in rendered application frames. The so-determined motion is then used to generate “spacewarped” versions of the rendered application frames.

Abstract: A processing unit is provided which comprises volatile storage for storing machine learning data in binary representation, and a data processing engine communicatively coupled to the volatile storage. The processing unit is configured to selectively invert the bit values in binary representations of portions of the machine learning data when performing storage operations using the volatile storage. A computer-implemented method, and non-transitory computer-readable storage medium comprising instructions for executing the method are also provided. The method comprises receiving a request to perform a storage operation on the volatile storage using the machine learning data and performing the storage operation, including, selecting a portion of the machine learning data and inverting bit values in a binary representation of the selected portion. A computer-implemented method comprising receiving a request to store machine learning data on volatile storage and storing the machine learning data is also provided.

Abstract: A data processing system operable to process a neural network, and comprising a plurality of processors. The data processing system is operable to determine whether to perform neural network processing using a single processor or using plural processors. When it is determined that plural processors should be used, a distribution of the neural network processing among two or more of the processors is determined and the two or more processors are each assigned a portion of the neural network processing to perform. A neural network processing output is provided as a result of the processors performing their assigned portions of the neural network processing.

Abstract: A navigation system uses markers that are identifiable in images of an environment being navigated to determine the location of a portable device in the environment. The portable device takes images of the environment, and those images are analysed to identify markers in the images and the pose of the portable device based on the image of the marker. The identified marker and the determined pose of the portable device are then used to determine the location and orientation of the portable device in the environment being navigated.

Abstract: An extended-reality system is described which determines extended-reality data to be obtained from the remote network-connected storage based on a location of the extended-reality system. The extended-reality system determines a communication method by which to obtain the extended-reality data, wherein the extended-reality data may be obtained by one or more requests to the remote network-connected storage or by one or more requests to a local device outside of the extended-reality system. A request is sent to at least one of the local device via a peer-to-peer network and the remote network-connected storage in dependence upon the determination by the extended-reality system.

Abstract: A device comprising a first side for facing a user of the device, a second side opposite to the first side, a sensor operable to output gaze data representative of a gaze direction of the user, a display device and at least one processor. The at least one processor is configured to control the display device to control display of an image intended to be displayed on the second side of the device on the basis of the gaze data in order to reduce light being directed towards a pupil of the user from the first side of the device by the display of the image. Also described is a method of controlling such a device.

Abstract: When rendering a new frame using a hybrid ray tracing process, a graphics processor transforms vertex position data for models representing objects in the new frame into camera space for use in a rasterisation process of the hybrid ray tracing process irrespective of whether the object has moved between frames or whether the geometry of the model representing object has changed, but only transforms vertex position data for a model for an object into world space for use in a ray tracing process of the hybrid ray tracing process when the object has moved between frames or where the geometry of the model representing the object has changed.