Abstract: A head-mountable display (HMD) system includes at least one detector to detect movement of an eye of a user wearing the HMD, control circuitry to detect saccadic movement of the eye in dependence upon the detected movement of the eye, a display unit and a processor to generate images for display to the user by the display unit, in which the control circuitry is configured to control the processor in response to the detected saccadic movement, in which the control circuitry is configured to control the processor to adjust one or more image quality parameters for one or more of the images to be displayed by the display unit during the detected saccadic movement.

Abstract: An image rendering method the steps of, for a view of a virtual model having a locus of interest, performing flexible scale rasterisation with a first bin distribution for a luminance channel, and mapping the results to a first pixel space; performing flexible scale rasterisation with a second bin distribution for chrominance channels, and mapping the results to a second pixel space; and outputting an image based upon the luminance and chrominance results mapped to the first and second pixel spaces; where the second bin distribution includes larger bins than the first bin distribution in a region outside the locus of interest.

Abstract: An encoding apparatus is provided. The apparatus comprises an input unit operable to obtain a plurality of training images, said training images being for use in training a machine learning model. The apparatus also comprises a label unit operable to obtain a class label associated with the training images; and a key unit operable to obtain a secret key for use in encoding the training images. The apparatus further comprises an image noise generator operable to generate, based on the obtained secret key, noise for introducing into the training images. The image noise generator is configured to generate noise that correlates with the class label associated with the training images such that a machine learning model subsequently trained with the modified training images learns to associate the introduced noise with the class label for those images. A corresponding decoding apparatus is also provided.

Abstract: A system for adjusting the pose of a camera relative to a subject in a scene is provided. The system comprises a camera operable to capture images of a scene; an identification unit configured to identify an object of interest in images of the scene; a pose processor configured to obtain a pose of the object of interest in the scene relative to the camera; a scene analyser operable to determine, based on at least one of the obtained pose of the object of interest and images captured by the camera, a scene quality associated with images captured by the camera. A controller is configured to cause the pose of the camera to be adjusted based on a determination that the scene quality of an image captured at a current pose is less than a threshold value. A corresponding device is also provided.