Abstract: A method comprising detecting, by a processor, an optical sight of a device in range of a lens of a head mounted display (HMD) apparatus. The lens has an HMD field of view (H-FOV) of a real-world view. The method comprises determining, by the processor, a magnification factor of a sight field of view (S-FOV) for the detected sight. The method includes displaying, by a display device of the HMD apparatus, computer generated data (CGD) in the S-FOV relative to a magnification level according to the magnification factor of the S-FOV of the real-world view while looking through the sight. A system and computer readable medium are also provided.

Abstract: A display panel driver includes a scaler circuit performing image enlargement processing on input image data corresponding to an input image to generate ?-times enlarged image data corresponding to an ?-times enlarged image (? is a number larger than one which cannot be represented as 2k); and a driver section driving a display panel. In calculating a pixel value of a target pixel of the ?-times enlarged image, the scaler circuit generates enlarged image data including 2n-times enlarged image data corresponding to a 2n-times enlarged image obtained by enlarging the input image with an enlargement factor of 2n (n is the smallest integer determined so that 2n is larger than ?), and calculates the pixel value of the target pixel from the 2n-times enlarged image data through interpolation processing of pixel values of pixels of the 2n-times enlarged image corresponding to the target pixel of the ?-times enlarged image.

Abstract: An image processing apparatus includes an image acquirer configured to acquire an input image, and a processor configured to generate the original image by performing for the input image correction processing using correction data according to an optical aberration of the observation optical system. In the correction processing for the oblique view state, the processor uses first correction data according to the optical aberration corresponding to a first position distant from the observation optical system by a distance made by adding a rotating radius of the eye to the first distance, to generate an area other than the specific area in the original image, and uses second correction data according to the optical aberration corresponding to a second position closer to the observation optical system than the first position to generate the specific area.

Abstract: An image processing method is described. The method includes obtaining low dynamic range expansion exponents ELDR(p), obtaining target expansion exponents ET(p) as a weighted sum of the high dynamic range expansion exponents EHDR(p) and of the low dynamic range expansion exponents ELDR(p), applying obtained target expansion exponent ET(p) to low dynamic range luminance values YLDR of a low dynamic range version of the image, resulting in target luminance values YT, and building a tone-adapted version of said image based on said target luminance values YT.

Abstract: The present disclosure relates to a method and apparatus for determining an illumination intensity for inspection, and an method and apparatus optical inspection. The method for determining an illumination intensity for inspection comprises: acquiring images of a sample to be inspected taken by each of at least one imaging element at a plurality of illumination intensities; calculating, for each imaging element, a gray standard deviation of each of the images acquired at the plurality of illumination intensities; and determining the illumination intensity of each imaging element for inspection according to the gray standard deviation. The inspection accuracy may be improved by using the illumination intensity determined by the method provided in the present disclosure to inspect an object to be inspected.

Abstract: Techniques are described for performing estimations based on image analysis. In some implementations, one or more images may be received of at least portion(s) of a physical object, such as a vehicle. The image(s) may show damage that has occurred to the portion(s) of the physical object, such as damage caused by an accident. The image(s) may be transmitted to an estimation engine that performs pre-processing operation(s) on the image(s), such as operation(s) to excerpt one or more portion(s) of the image(s) for subsequent analysis. The image(s), and/or the pre-processed image(s), may be provided to an image analysis service, which may analyze the image(s) and return component state information that describes a state (e.g., damage extent) of the portion(s) of the physical object shown in the image(s). Based on the component state information, the estimation engine may determine a cost estimate to repair and/or replace damaged component(s).

Abstract: Systems and methods for generating a mask for automated assessment of embryo quality are disclosed herein. The method for generating a mask for automated assessment of embryo quality can include receiving an image, including a plurality of pixels, of a human embryo from an imaging system. A pixel can be selected and features of the selected pixel can be determined by generating a plurality of random boxes of random sizes and at random locations about the selected pixel. The selected pixel can be identified as one of: inside of a mask area; and outside of the mask area based on the determined features.

Abstract: An image processing system connected to an endoscope and processing in real-time endoscopic images to identify suspicious tissues such as polyps or cancer. The system applies preprocessing tools to clean the received images and then applies in parallel a plurality of detectors both conventional detectors and models of supervised machine learning-based detectors. A post processing is also applied in order select the regions which are most probable to be suspicious among the detected regions. Frames identified as showing suspicious tissues can be marked on an output video display. Optionally, the size, type and boundaries of the suspected tissue can also be identified and marked.

Abstract: A medical image comparison method is firstly to obtain plural images of the same body at different time points. Then, obtain a first feature point group by detecting feature points in the first image captured at a first time point, and a second feature point group by identifying feature points in the second image captured at a second time point. An overlapping image information is generated by aligning the second image with the first image according to the first and second feature point groups. Then, window areas corresponding to a first matching image and a second matching image of the overlapping image information are extracted one by one by sliding a window mask, and an image difference ratio for each of the window areas is calculated. In addition, a medical image comparison system is also provided.

Abstract: A method for processing an input in an artificial neural network (ANN) includes receiving, at an operator layer of a set of operator layers, a first feature value based on the input from a decoder convolutional layer of a decoder. The operator layer also receives a second feature value based on the input from an encoder convolutional layer of a encoder. The method also includes determining, at the operator layer, a third feature value based on the input by performing an element-wise operation with the first feature value based on the input and the second feature value based on the input. The method transmits, from the operator layer, the third feature value based on the input to an encoder layer that is subsequent to the encoder convolutional layer. The method generates an output based on the third feature value based on the input.

Abstract: An image processing device includes: a plurality of label data generation units which generate label data in which a predetermined label is assigned to each of a plurality of pixels in each of a plurality of divided images; a plurality of label integration information generation units which correspond to the respective label data generation units and generate label integration information representing association of labels included in the label data in order to integrate label data generated by a corresponding label data generation unit and label data generated by another label data generation unit; a plurality of label integration units which generate integrated label data in which respective pieces of label data corresponding to neighboring divided images are integrated; and a label integration processing control unit which distributes the label data to the respective label integration units such that computational loads to integrate the label data are equalized.

Abstract: Methods and systems which provide object edge image representation generation using block based edgel techniques implementing post edgel detection processing to eliminate false edges are described. Embodiments subdivide image data (e.g., image point clouds) to facilitate separate edgel detection processing of a plurality of sub-blocks of the image data. A false edge elimination algorithm of embodiments is applied in recombining the object edge image representation sub-blocks resulting from the sub-block edgel detection processing to eliminate false edge artifacts associated with use of block based edgel detection.

Abstract: Techniques are described for generating a distance map (e.g., a map of disparity, depth or other distance values) for image elements (e.g., pixels) of an image capture device. The distance map is generated based on an initial distance map (obtained, e.g., using a block or code matching algorithm) and a segmentation map (obtained using a segmentation algorithm). In some instances, the resulting distance map can be less sparse than the initial distance map, can contain more accurate distance values, and can be sufficiently fast for real-time or near real-time applications. The resulting distance map can be converted, for example, to a color-coded distance map of a scene that is presented on a display device.

Abstract: A method of tracking a cell through a plurality of images includes selecting the cell in at least one image obtained at a first time, generating a track of the cell through a plurality of images, including the at least one image, obtained at different times using a backward tracking, and generating a cell tree lineage of the cell using the track.

Abstract: Aspects of the disclosure generally relate to determining the location and orientation of panoramic images by a computing apparatus. One or more computing devices may receive alignment data between a first panoramic image and second panoramic image and original location data for the first panoramic image and the second panoramic image. The one or more computing devices may determine relative orientations between the pair of panoramic images based on the alignment data and calculate a heading from the first panoramic image to the second panoramic image based on the original location data. The location data and alignment data may be optimized by the one or more computing devices based on the relative orientations between the pair of panoramic images and the original location data. The one or more computing devices may replace the original location data and relative orientations with the optimized relative orientations and optimized location data.

Abstract: A computer-implemented method for determining whether a first image contains at least a portion of a second image includes: determining a first set of feature points associated with the first image; removing from said first set of feature points at least some feature points in the first set that correspond to one or more textures in the first image; and then attempting to match feature points in said first set of feature points with feature points in a second set of feature points associated with said second image to determine whether said first image contains at least a portion of said second image.

Abstract: Devices, systems and methods are disclosed for performing image processing at a camera-level. For example, a camera service may run on top of a camera hardware abstraction layer (HAL) and may be configured to perform image processing such as applying a blurring algorithm, applying a color filter and/or other video effects. An application may pass metadata to the camera service via an application programming interface (API) and the camera service may use the metadata to determine parameters for the image processing. The camera service may apply the blurring algorithm for a first period of time before transitioning to unblurred image data over a second period of time.

Abstract: Machine vision processing includes capturing 3D spatial data representing a field of view and including ranging measurements to various points within the field of view, applying a segmentation algorithm to the 3D spatial data to produce a segmentation assessment indicating a presence of individual objects within the field of view, wherein the segmentation algorithm is based on at least one adjustable parameter, and adjusting a value of the at least one adjustable parameter based on the ranging measurements. The segmentation assessment is based on application of the segmentation algorithm to the 3D spatial data, with different values of the at least one adjustable parameter value corresponding to different values of the ranging measurements of the various points within the field of view.

Abstract: A method and system for processing camera images is presented. The system receives a first depth map generated based on information sensed by a first type of depth-sensing camera, and receives a second depth map generated based on information sensed by a second type of depth-sensing camera. The first depth map includes a first set of pixels that indicate a first set of respective depth values. The second depth map includes a second set of pixels that indicate a second set of respective depth values. The system identifies a third set of pixels of the first depth map that correspond to the second set of pixels of the second depth map, identifies one or more empty pixels from the third set of pixels, and updates the first depth map by assigning to each empty pixel a respective depth value based on the second depth map.

Abstract: Methods and apparatus for estimating a depth of unfocused plenoptic data are suggested. The method includes: determining a level of homogeneity of micro-lens images of unfocused plenoptic data; determining pixels of the micro-lens images of the unfocused plenoptic unfocused plenoptic data which either have disparities equal to zero or belong to homogeneous areas as a function of the calculated level of homogeneity of the micro-lens images of the unfocused plenoptic data; and estimating the depth of the unfocused plenoptic data by a disparity estimation without considering the determined pixels. With the disclosure, by pre-processing the raw data, it can prevent any disparity estimation method to spend time on estimating disparities for: (i) pixels that are in focus, (ii) pixels that belong to homogenous areas of the scene.

Abstract: Embodiments described herein provide various examples of a real-time face-detection, face-tracking, and face-pose-selection subsystem within an embedded video system. In one aspect, a process for performing real-time face-pose-estimation and best-pose selection for a detected person captured in a video is disclosed. This process includes the steps of: receiving a video image among a sequence of video frames of a video; performing a face detection operation on the video image to detect a set of faces in the video image; detecting a new person appears in the video based on the set of detected faces; tracking the new person through subsequent video images in the video by detecting a sequence of face images of the new person in the subsequent video images; and for each of the subsequent video images which contains a detected face of the new person being tracked: estimating a pose associated with the detected face and updating a best pose for the new person based on the estimated pose.

Abstract: Systems and methods related to identifying locations and/or ranges to objects using airborne imaging devices are disclosed. An object tracking system may include a plurality of aerial vehicles having associated imaging devices and a control station. Information related to positions and orientations of aerial vehicles and associated imaging devices may be received. In addition, imaging data may be received and processed to identify optical rays associated with objects within the imaging data. Further, a three-dimensional mapping of the identified optical rays may be generated, and locations or ranges of the objects relative to the aerial vehicles may be determined based on any intersections of optical rays within the three-dimensional mapping.

Abstract: An information processing apparatus comprising: a marker detection unit configured to detect one or more markers from an image obtained by capturing a physical space by an image capturing unit; a feature detection unit configured to detect a feature from the image; an estimation unit configured to estimate a position and orientation of the image capturing unit based on a detection result obtained by the marker detection unit and a detection result obtained by the feature detection unit; a stability obtaining unit configured to obtain stability of estimation of the position and orientation when some markers of the one or more markers are removed; and a determination unit configured to determine, based on the stability, whether the some markers are removable.

Abstract: A Dynamic Vision Sensor (DVS) pose-estimation system includes a DVS, a transformation estimator, an inertial measurement unit (IMU) and a camera-pose estimator based on sensor fusion. The DVS detects DVS events and shapes frames based on a number of accumulated DVS events. The transformation estimator estimates a 3D transformation of the DVS camera based on an estimated depth and matches confidence-level values within a camera-projection model such that at least one of a plurality of DVS events detected during a first frame corresponds to a DVS event detected during a second subsequent frame. The IMU detects inertial movements of the DVS with respect to world coordinates between the first and second frames. The camera-pose estimator combines information from a change in a pose of the camera-projection model between the first frame and the second frame based on the estimated transformation and the detected inertial movements of the DVS.

Abstract: An apparatus for use in a medical procedure includes: a camera configured for attachment to a patient, wherein the camera is configured to detect one or more markers outside and away from the patient; and a processing unit configured to receive an input image from the camera, and to process the input image to monitor a position of a target associated with the patient during the medical procedure. An apparatus for use in a medical procedure includes: a camera configured for attachment to a patient support, wherein the camera is configured to detect one or more markers outside and away from the patient support; and a processing unit configured to receive an input image from the camera, and to process the input image to determine a position associated with the patient support during the medical procedure.

Abstract: A computer-implemented method of calibrating a camera, comprises the steps of: a. acquiring a video stream from said camera (CAM), and displaying it on a screen (DY); b. displaying on the screen, superimposed to the video stream, a representation of a target area (102); c. detecting a calibration pattern (100) in the video stream and periodically check whether it fits within the calibration area; d. when the calibration pattern is found to fit within the calibration area, extracting an image thereof from the video stream; said steps a. to d. being iterated a plurality of times using respective target areas corresponding to different positions of a physical support (101) carrying the calibration pattern; and then e. estimating intrinsic calibration parameters of the camera by processing said images. A computer program product, computer-readable data-storage medium and computer system for carrying out such a method.

Abstract: According to an embodiment, an image processing apparatus includes a matching unit configured to perform stereo matching processing on two images obtained through imaging using two cameras, an error map creating unit configured to create an error map indicating a displacement amount of the two images in a direction orthogonal to a search line for the two images subjected to the stereo matching processing, and a parallelization parameter error determining unit configured to determine whether or not there is an error of rectification which parallelizes the two images, based on the error map.

Abstract: A processing unit, method, and medium for decompressing or generating textures within a graphics processing unit (GPU). The textures are compressed with a variable-rate compression scheme such as JPEG. The compressed textures are retrieved from system memory and transferred to local cache memory on the GPU without first being decompressed. A table is utilized by the cache to locate individual blocks within the compressed texture. A decompressing shader processor receives compressed blocks and then performs on-the-fly decompression of the blocks. The decompressed blocks are then processed as usual by a texture consuming shader processor of the GPU.

Abstract: Techniques for compressing images based on context are provided. A first image and a second image may be identified for display on a client device. One or more contexts of the first image may be identified. One or more contexts of the second image may be identified. A first image quality for the first image may be determined based on the one or more contexts of the first image. A second image quality for the second image may be determined based on the one or more contexts of the second image. The first image may be compressed at the first image quality and the second image at the second image quality. The compressed first image and the compressed second image may be transmitted to the client device.

Abstract: A method for the reconstruction of image data based upon a plurality of multi-energy projection measurement data sets of a field of examination of an object under examination is described. In an embodiment of the method, a plurality of projection measurement data sets, produced via multi-energy CT imaging using differing X-ray energy spectra of the field of examination of the object under examination, are captured. In addition, a reduced number of image data sets are produced based upon the plurality of projection measurement data sets by applying a basic material decomposition and an image mix. An image data reconstruction facility is also described. Furthermore a computed tomography system is described.

Abstract: In some examples, a system may receive log data including a depth-series of data for a sensed parameter. The system may determine a parameter value of the depth series data for individual subunits of depth corresponding to a larger unit of depth. The system may further determine a scale of graphic effects corresponding to parameter values for the depth-series data. The system may present, on a display, a visualization of the depth-series data. For instance, the visualization may include a plurality of cells arranged in a plurality of rows, with each cell corresponding to the larger unit of depth and including a plurality of subcells corresponding to the subunits of depth. Additionally, each subcell may be presented with a respective graphic effect corresponding to the parameter value determined at a corresponding depth, and the graphic effect may correspond to the parameter value on the scale of graphic effects.

Abstract: Disclosed are a method for editing a character image in a character image editing apparatus and a recording medium having a program recorded thereon for executing the method. The present invention is implemented through processes of enabling a character image editing apparatus to take, as an input, character information and to generate a dot image at the position corresponding to the position of the margin on the character image relevant to the input character information. According to the present invention, a development of a design can be easily performed in various articles, art work, building, craftwork, city planning in which characters such as Hangul are represented. In addition, according to the present invention, a development of industrial products with symbolized characters such as Hangul can be promoted in a variety of fields such as industry, art, design, construction, handicraft, and city planning.

Abstract: Disclosed are systems and methods for using a hands free computing device. The device includes a processor, a head movement measuring component, screen, camera, microphone, and memory. Responsive to sensing an instruction by a user, an image is captured by the camera and displayed on the screen. There is recorded, using the microphone, an audible catch phrase provided by the user for the image. The audible catch phrase is converted to text that is superimposed on the image thereby making a fused image. The user identifies one or more remote recipients of the fused image. The fused image is communicated, with the text phrase formatted for scrambled display, to the one or more remote recipients. The fused image is displayed on remote devices associated with such recipients with the text phrase scrambled.

Abstract: An electronic device is provided. The electronic device includes a memory to store a plurality of images which are discontinuously captured and a processor to select at least some of the plurality of images, generate an image combination file in a format for sequentially playing the selected images by combining the selected images, and store the image combination file in the memory. The device can further provide a display to add, delete and arrange images of the image combination files.

Abstract: Described embodiments include a system that includes a display and a processor. The processor is configured to modify an image slice by filling a portion, of the image slice, that corresponds to an anatomical cavity with a representation of a wall of the anatomical cavity, and to display the modified image slice on the display. Other embodiments are also described.

Abstract: A visualization combination engine may be used to combine a first data visualization based on a first data set with a second data visualization based on a second data set. The combination process may be initiated by, for example, clicking and dragging the first data visualization onto the second data visualization. The visualization combination engine may create the combined data visualization without requiring the user to manually combine the first and second data sets. The combination may be carried out by identifying a key that is common between the two data sets and combining the first and second data sets into a combined data set based on the key, and then creating the combined data visualization based on the combined data set. One or more cues may be used during the process to provide helpful information and/or allow user selection of the properties of the combined data visualization.

Abstract: Various embodiments provide an image processing method. The method may include: acquiring an input image (310); extracting a light source parameter from the input image (330); adjusting color of a material image according to the light source parameter, obtaining an adapted material image matching the input image using a binarization processing according to the material image whose color has been adjusted (350); obtaining a flare effect image through calculation using the adapted material image according to the light source parameter (370); and blending the input image with the flare effect image (390). An image processing apparatus is also provided. The above method and image processing apparatus can adapt a simulated flare effect to a light source in an image, and can improve the sense of realism.

Abstract: Technologies related to generating mixed reality video are described herein. Video frames capture a human, and positions of skeletal features of the human are estimated based solely upon the video frames. A mixed reality video is generated, wherein the mixed reality video includes the video combined with an animation, wherein the animation is based upon movement of the human in the video as represented by the estimated positions of the skeletal features of the human.

Abstract: The present disclosure provides example methods for changing graphics processing resolution according to a scenario. In one example, a first display scenario is determined as a scenario in which energy can be saved. Based on the determination, a graphics processing resolution of a graphics processor can be reduced. At least one target graphics frame in the first display scenario can be rendered by the graphics processor according to the reduced graphics processing resolution to obtain at least one target image frame. The at least one target image frame can be adapted according to screen display resolution, and the at least one adapted target image frame can be displayed. The present disclosure further provides a portable electronic device and a system for changing graphics processing resolution according to a scenario.

Abstract: A mobile telephone receives, constructs and displays an image from a server over a mobile telephone network. The server determines the parameters for data transfer from the server to the mobile telephone, the capabilities of the mobile telephone, transfer task requirements, and apportions the processing between the server and the mobile telephone for each of a plurality of elements in each image, thereby to meet the task requirement, which can include being within a predetermined time for task completion, or being the fastest means for task completion. Parameters for data transfer from server to telephone include server transmission bandwidth, phone reception bandwidth, data channel bandwidth, transmission protocol, and channel accessibility. Phone capabilities include the data processing speed, the available memory, display size, and the data processing software available; Task requirements include the maximum transmission time and the minimum display resolution of the image.

Abstract: A data processing device applies pattern data to surface data on the basis of projection data, subdividing the surface data into voxels and determining the optimum projection data for each voxel according to its surroundings.

Abstract: An exemplary volumetric reconstruction system accesses captured color and depth data for a surface of an object in a real-world capture space. The captured color and depth data is captured by capture devices positioned with respect to the real-world capture space to have different vantage points of the surface of the object. Based on the captured color and depth data, the volumetric reconstruction system generates reconstructed color and depth data for a volumetric reconstruction of the surface of the object. The generating of the reconstructed color and depth data includes allocating voxel nodes for surface points on the object within a voxel data store, determining and storing a confidence field value for each voxel node that accounts for a distance factor and a noise-reduction factor, and determining the reconstructed color and depth data using a raytracing technique based on the stored confidence field values within the voxel data store.

Abstract: A method and device for enriching the content associated with a first element of a depth map, the depth map being associated with a scene according to a point of view. Thereafter, at least a first information representative of a variation of depth in the first element in the space of the depth map is stored into the depth map.

Abstract: Methods, systems, and apparatus for obtaining first image features derived from an image of an object, providing the first image features to a three-dimensional estimator neural network, and obtaining, from the three-dimensional estimator neural network, data specifying an estimated three-dimensional shape and texture based on the first image features. The estimated three-dimensional shape and texture are provided to a three-dimensional rendering engine, and a plurality of three-dimensional views of the object are generated by the three-dimensional rendering engine based on the estimated three-dimensional shape and texture. The plurality of three-dimensional views are provided to the object recognition engine, and second image features derived from the plurality of three-dimensional views are obtained from the object recognition engine. A loss is computed based at least on the first and second image features, and the three-dimensional estimator neural network is trained based at least on the computed loss.

Abstract: A clip-cull-viewport (CCV) unit manages information associated with vertices of a primitive as the primitive passes through the CCV unit. The CCV unit includes an index cache and a cache-status table. Vertices of a received primitive are stored in locations within the index cache based on attribute and index fields of the primitive. If a vertex is a reused vertex of another primitive that matches a valid entry in the cache-status table and if the primitive survives being culled, the valid entry in the cache-status table is preserved, the attribute field of the primitive is set to indicate that the vertex is a reused vertex, and the primitive is sent to an output interface for a downstream unit. Otherwise, the attribute field is set to indicate that the vertex is not reused, and the primitive is sent to the output interface for the downstream unit.

Abstract: A graphics processing system includes a tiling unit for performing tiling calculations and a hidden surface removal (HSR) unit for performing HSR on fragments of the primitives. Primitive depth information is calculated in the tiling unit and forwarded for use by the HSR unit in performing HSR on the fragments. This takes advantage of the tiling unit having access to the primitive data before the HSR unit performs the HSR on the primitive fragments, to determine some depth information which can simplify the HSR performed by the HSR unit. Therefore, the final values of a depth buffer determined in the tiling unit can be used in the HSR unit to determine that a particular fragment will be subsequently hidden by a fragment of a primitive which is yet to be processed in the HSR unit, such that the particular fragment can be culled.

Abstract: Graphics processing includes setting up a plurality of objects in a scene in virtual space, each object being defined by a set of vertices. A unique object identifier is assigned to each object and written to an ID buffer. Draw calls are issued to draw the objects associated with the object identifiers. Parameter values of the vertices are manipulated to output vertex parameter values. Primitives are set up from the vertices, each primitive being defined by one or more of the vertices. Each primitive belongs to one or more of the objects. Each primitive is rasterized at a plurality of pixels. Processing the pixels includes spatial or temporal anti-aliasing that utilizes the one or more object identifiers of the plurality of object identifiers. The pixels are processed for each rasterized primitive to generate an output frame.

Abstract: A method includes: dividing the 3D virtual scene by using a plurality of grids; acquiring location information about a plurality of first points at which a plurality of rays originating from a light source are incident on one or more objects located within the 3D virtual scene and location information about a plurality of first grids including the plurality of first points; acquiring location information about a plurality of second points at which the plurality of rays reflected from the plurality of first points are incident on the one or more objects and location information about a plurality of second grids including the plurality of second points; and determining illumination of each of the plurality of grids based on the location information about the plurality of first grids and the location information about the plurality of second grids.

Abstract: A technique for performing rasterization and pixel shading with decoupled resolution is provided herein. The technique involves performing rasterization as normal to generate fine rasterization data and a set of (fine) quads. The quads are accumulated into a tile buffer and coarse quads are generated from the quads in the tile buffer based on a shading rate. The shading rate determines how many pixels of the fine quads are combined to generate coarse pixels of the coarse quads. Combination of fine pixels involves generating a single coarse pixel for each such fine pixel to be combined. The positions of the coarse pixels of the coarse quads are set based on the positions of the corresponding fine pixels. The coarse quads are shaded normally and the resulting shaded coarse quads are modified based on the fine rasterization data to generate shaded fine quads.

Abstract: Techniques for intuitive modifications of digital graphics in a digital media environment are described. For example, a digital graphics creation system accesses vector artwork including a vector object, such as a Bezier curve. The digital graphics creation system receives user inputs, including a user input defining handles on the vector object and a user input interacting with the handles indicating a desired change to the vector object. The digital graphics creation system modifies the vector artwork, including the vector object, by accounting for topology of the vector object and maintaining connections between connected segments of the vector object. The digital graphics creation system outputs the modified vector artwork, including the vector object, such as in a user interface.