Abstract: A method includes displaying an image on a first area of a touch-sensitive electronic display and receiving touch input on a second area of the display, comprising the first area. A gesture type is detected from the touch input by detecting a larger component of motion of the touch input along one of first and second axes of the display than along the other of the axes. Detecting a second gesture type comprises detecting a larger component of motion of the touch input along the other of the axes than along the one of the axes. If the gesture type is the first gesture type, a display characteristic of the image is adjusted, during displaying the image. If the gesture type is the second gesture type, the display ceases to display the image and displays a further image. A computing system is provided.

Abstract: A method of processing image data representative of at least part of an image using a computing system to detect at least one class of object in the image. The method comprises processing the image data using a neural network system selected from a plurality of neural network systems including a first neural network system arranged to detect a class of objects, and a second neural network system arranged to detect the class of objects. The first neural network system comprises a first plurality of layers and the second neural network system comprises a second plurality of layers. The second neural network system has at least one of: more layers than the first neural network system; more neurons than the first neural network system; and more interconnections between neurons than the first neural network system. The method comprises obtaining a trigger and, on the basis of the trigger, processing the image data using a selected one of the first and second neural network systems.

Abstract: Examples of the present disclosure relate to a method for reducing artefacts caused by the presence of flicker during capture of a video. A sequence of frames of the video are captured, the frames each comprising a plurality of predefined regions each comprising a plurality of pixels. A time-varying oscillation of the flicker is characterized based on variations, across the sequence of frames, of data relating to pixel intensities in at least one said region. Based on the characterizing of the time-varying oscillation of the flicker, a flicker correction is applied to a frame of the video.

Abstract: Examples of the present disclosure relate to an image processing apparatus comprising a filter to convert a first image data signal into an output image data signal. The filter is configured to resample the first image data signal, having a first sample rate, by a resampling factor, such that the output image data signal has an output sample rate that is different to the first sample rate. The filter is also configured to apply a phase alteration to the first image data signal to compensate a group delay in the first image data signal.

Abstract: Examples of the present disclosure relate to methods for performing object detection. In one such example, data representing an image is received. The image comprises at least one target region and a further region. The at least one target region is identifiable using data indicative of a gaze direction of a viewer of the image. A first portion of the data is processed using a first processing scheme to perform object detection in the at least one target region of the image. The first portion of the data represents the at least one target region of the image. A second portion of the data is processed using a second, different, processing scheme. The second portion of the data represents the further region of the image.

Abstract: A method of processing image data representative of an image using a multi-stage system comprising a first neural network (NN) for identifying a first image characteristic and a second NN for identifying a second image characteristic. The method comprises processing the image data using t a first at least one layer of the first NN to generate feature data representative of at least one feature of the image and processing the feature data using a second at least one layer of the first NN to generate first image characteristic data indicative of whether the image includes the first image characteristic. The feature data is transferred from the first NN to the second NN. The feature data is processed using the second NN to generate second image characteristic data representative of whether the image includes the second image characteristic.

Abstract: Examples of the present disclosure relate to methods for processing image data. In one such example, first data representing a rendered image is received. In some cases, second data useable to identify at least one target region of the rendered image is received, the at least one target region being associated with a gaze direction of a viewer. A first portion of the first data is processed in accordance with a first data reduction rate to derive first processed data, the first portion representing the at least one target region. A second portion of the first data is processed in accordance with a second data reduction rate, different from the first data reduction rate. The second portion represents a further region of the rendered image, different from the at least one target image. At least the first processed data is outputted.

Abstract: Examples of the present disclosure relate to methods for processing image data. In one such example, data elements are received defining a portion of a line of pixels of an image, the image comprising one or more lines of pixels definable by one or more respective sets of data elements. In some cases, a transform operation is performed on the data elements to obtain a plurality of binary transform coefficients, wherein the transform operation is performed independently of data elements defining any other line of pixels. The plurality of transform coefficients is encoded as a sequence of tiered bit-layers, each bit-layer in the sequence of bit-layers comprising a set of bits corresponding to a given bit position in each of the plurality of transform coefficients. The encoded plurality of transform coefficients is output.

Abstract: Examples of the present disclosure relate to methods for controlling a display device. In one such example, data representing a result of an eyewear detection operation is obtained. Dependent on the obtained data, a control signal is outputted to adjust a display parameter of the display device. Performing the eyewear detection operation comprises receiving image data representing a user of the display device, and processing the image data using object recognition to determine whether or not the user is wearing eyewear of a predetermined type.

Abstract: A method comprising, in an image processing operation, identifying location data indicative of a read path for the image processing operation, the read path at least partly traversing a block of pixels of an image. Parameter data relating to a characteristic of the read path in the context of the block is generated from the location. Storage prioritization data is associated with the block at least partly on the basis of the parameter data. The storage prioritization data is for determining whether block data representative of the block is to be evicted from storage.

Abstract: Image data representative of at least a portion of an image comprising first and second sets of pixels associated with first and second colour channels, respectively, is received. It is determined that a first pixel of the first set of pixels is a saturated pixel. First data based on a value of the first pixel of the second set of pixels is obtained for a first image region comprising the first pixel of the first set of pixels and a first pixel of the second set of pixels. Second data based on respective values of second pixels of the first and second sets of pixels are obtained, based on the first data, for a second image region. The second data is processed to generate output data representative of an estimated value associated with the first colour channel for the first pixel.

Abstract: A method of processing input data using a computing system. The method comprises obtaining association data which relates a kernel in a convolutional neural network to one or more known data patterns; conducting analysis of input data for the convolutional neural network to identify whether a region of input data corresponds to at least one of the one or more known data patterns; and determining whether to process the region of input data with the kernel in the convolutional neural network based on the analysis and the association data.

Abstract: A method of processing video data representative of a video. A feature of a first frame of the video is identified by performing a feature detection operation in a first and second portion of the first frame. Subsequently, a feature of a second frame of the video is identified by processing the second frame to identify a first portion of the second frame which changed with respect to the first portion of the first frame, a second portion of the second frame which is substantially unchanged with respect to the second portion of the first frame, and a third portion of the second frame which is substantially unchanged with respect to a third portion of the first frame. The feature detection operation is performed in the first and third portions of the second frame and omitted in the second portion of the second frame.

Abstract: A method for reducing artefacts caused by the presence of flicker during image capture. The method comprises performing image capture to produce image capture data corresponding to an image capture scene, the image capture data including a first image having a first exposure and a second image having a second exposure. The image capture data is processed to: (a) detect a discrepancy in the second image with respect to the first image; and (b) determine flicker indication data indicative of a presence of flicker in the second image. The discrepancy is corrected in dependence upon the flicker indication to produce a flicker-reduced version of the second image.

Abstract: A method including receiving input data representing an input frame of a video. Transformation data representing at least one transformation for applying to an image to adjust a geometric distortion of the image is received. A first and second plurality of input tiles, each including a respective portion of the input frame, is processed with at least part of the transformation data, thereby generating first and second sub-window data representing a first and second sub-window of an output frame of the video, respectively.

Abstract: A storage system comprising storage including a plurality of storage banks and a storage controller to control writing of received pixel data to the storage banks in a distribution pattern. The distribution pattern includes pattern sections, each of which corresponds to pixels from a row of input pixels, and pattern blocks, each of which corresponds to pixels from a plurality of adjacent rows and columns of the input pixels. Pixel data in a pattern section and a pattern block are each written to different ones of the storage banks. The pattern section includes a first section part, which overlaps the pattern block and a second section part, which does not overlap the pattern block. Pixel data of the first section part is written to a first set of storage banks and pixel data of the second section part is written to a second, different, set of storage banks.

Abstract: A method of forming a control parameter dependent on ambient light. The method comprises the steps of acquiring light values from an ambient light sensor and acquiring positional status values from a positional status sensor. The control parameter depends on the light values and is filtered in dependence on the positional status values.

Abstract: Methods of reducing digital video flicker, and related systems, devices and computer program products are provided. A method of reducing human-perceivable flicker in a digital video is provided, in which video frames are recorded unevenly with respect to time and in synchronization with a lighting flicker frequency. A system including a camera and a computer is provided, the system configured to reduce human-perceivable flicker in a digital video, in which video frames are recorded unevenly with respect to time and in synchronization with a lighting flicker frequency, so as to reduce human-perceivable flicker in a video assembled using the computer from the video frames.

Abstract: According to an aspect of the present disclosure, there is provided a method of image processing. The method comprises receiving image data comprising a set of feature vectors of a first dimensionality, the feature vectors corresponding to a class of objects. A variable projection is applied to each feature vector in the set of feature vectors to generate a set of projected vectors of a second dimensionality. The method then comprises processing the set of projected vectors to generate a model for the class of objects. A projection is applied to the model to generate an object classification model, of the first dimensionality, for the class of objects.

Abstract: The present disclosure provides an adaptive shading correction method for correcting an image for lens shading, including segmenting the image into a plurality of blocks of pixels and identifying hue-flat blocks with a relatively low hue variance, where the hue-flat blocks are clustered into at least one cluster based on a spatial distribution of the blocks. Selected modification parameters for modifying an average shading mesh are identified by modifying the average shading mesh along a plurality of dimensions using a plurality of modification parameters, and processing the at least one cluster with the average shading mesh as modified so as to identify the selected modification parameters. The average shading mesh is modified using the selected modification parameters to generate a shading correction mesh, which is used to correct the image for lens shading.