Abstract: A processor obtains an input image containing both bright and dark regions. The processor obtains a threshold between a first pixel value and a second pixel value of the display. Upon detecting a region of the input image having an original pixel value above the threshold, the processor can create a data structure including a location of the region in the input image and an original pixel value of the region. The data structure occupies less memory than the input image. The display presents the input image including the region of the image having the original pixel value above the threshold. The processor sends the data structure to a camera, which records the presented image. The processor performing postprocessing obtains the data structure and the recorded image and increases dynamic range of the recorded image by modifying the recorded image based on the data structure.

Abstract: Methods, an apparatus, and software media are provided for removing unwanted information such as moving or temporary foreground objects from a video sequence. The method performs, for each pixel, a statistical analysis to create a background data model whose color values can be used to detect and remove the unwanted information. The method assumes that for each pixel the background is present in a majority of the frames. The camera that records the video sequence may move relative to the geometry of the video scene. A pixel in a first frame is matched to a location in the geometry. The method determines color values of pixels, matched to the location in the geometry, in successive frames and clusters color values to determine a background color value range. It may use quadratic or better interpolation and extrapolation to determine background color values for unavailable frames.

Abstract: Methods, an apparatus, and software media are provided for removing unwanted information such as moving or temporary foreground objects from a video sequence. The method performs, for each pixel, a statistical analysis to create a background data model whose color values can be used to detect and remove the unwanted information. This includes determining a prevalent color cluster from among k clusters of color values for the pixel in successive frames. The method uses k-means clustering. To replace the unwanted information, the method iterates frames to find frames in which a pixel's color value is not included in the prevalent color cluster. In those frames, it replaces the pixel's color value with a value from the prevalent color cluster.

Abstract: Disclosed here are various techniques to increase dynamic range of an image recorded from a display. A processor performing preprocessing splits an input image containing both bright and dark regions into two images, image A containing bright regions, and image B containing dark regions. The display presents image A and image B in alternating fashion. Camera is synchronized with the display to record image A and image B independently. In postprocessing, a processor obtains the recorded images A and B. The processor increases the pixel value of the recorded image A to obtain image A with increased pixel value. Finally, the processor increases pixel value of the image recorded from the display by combining the first recorded image with increased pixel value and the second recorded image.

Abstract: Methods and systems are presented for generating a virtual scene rendering of a captured scene based on a relative position of a camera and a virtual scene display in a stage environment, along with real and virtual lens effects. The details might include determining the camera position and virtual display position in the stage environment, and determining a depth value of a virtual scene element displayed on the virtual scene display. A desired focus model can then be determined from focus parameters of the camera, the depth value, and a desired lens effect, and an adjusted focus for the virtual scene element can be determined from the desired focus model. The adjusted focus can then be applied to the camera, the image of the virtual scene element on the virtual scene display, or pixels representing the virtual scene element in a composite image captured by the camera.

Abstract: The disclosed system increases resolution of a display. The display operates at a predetermined frequency by displaying a first image at a first time and a second image at a second time. A selective screen disposed between the display and the camera includes multiple light transmitting elements. A light transmitting element A redirects a first portion of light transmitted by the display. A light transmitting element B allows a second portion of light transmitted by the display to reach the camera. The selective screen increases the resolution of the display by operating at the predetermined frequency and causing a first portion of the first image to be shown at the first time, and a second portion of the second image to be shown at the second time. The camera forms an image from the first portion of the first image, and the second portion of the second image.

Abstract: A representation of a surface in a three-dimensional space is obtained. A first input representing a starting point and a second input representing a next point are obtained. A representation of a surface-aware spline comprising vertices is generated, with the representation of the surface-aware spline including a starting vertex corresponding to the starting point and a next vertex corresponding to the next point. First and second projection points corresponding to projections of a first vertex and a second vertex onto the surface are determined. New points corresponding to equal distance points for the first and second vertices aligned with the first and second projection points are determined, and a rigid transformation is determined from the new points. The representation of the surface-aware spline is adjusted based on a transformation of the new points using the rigid transformation.

Abstract: In an image processing system, artist user interface provides for user input of specifications for an inserted object, specified in frame space. The inserted objects can be specified in frame space but can be aligned with object points in a virtual scene space. For other frames, where the object points move in the frame space, the object movements are applied to the inserted object in the frame space. The alignment can be manual by the user or programmatically determined.

Abstract: Disclosed here are various techniques to increase dynamic range of an image recorded from a display. A processor performing preprocessing splits an input image containing both bright and dark regions into two images, image A containing bright regions, and image B containing dark regions. The display presents image A and image B in alternating fashion. Camera is synchronized with the display to record image A and image B independently. In postprocessing, a processor obtains the recorded images A and B. The processor increases the pixel value of the recorded image A to obtain image A with increased pixel value. Finally, the processor increases pixel value of the image recorded from the display by combining the first recorded image with increased pixel value and the second recorded image.

Abstract: The processor obtains a first pixel value and a second pixel value of the display. The processor determines a desired pixel value range that exceeds the second pixel value of the display. The processor obtains a threshold between the first pixel value of the display and the second pixel value of the display. The processor obtains a function mapping the desired pixel value range to a range between the threshold and the second pixel value. The processor applies the first function to an input image prior to displaying the input image on the display. The display presents the image. Upon recording the presented image, the processor determines a region within the recorded image having a pixel value between the threshold and the second pixel value. The processor increases dynamic range of the recorded image by applying an inverse of the function to the pixel value of the region.

Abstract: The processor obtains a first pixel value and a second pixel value of the display. The processor determines a desired pixel value range that exceeds the second pixel value of the display. The processor obtains a threshold between the first pixel value of the display and the second pixel value of the display. The processor obtains a function mapping the desired pixel value range to a range between the threshold and the second pixel value. The processor applies the first function to an input image prior to displaying the input image on the display. The display presents the image. Upon recording the presented image, the processor determines a region within the recorded image having a pixel value between the threshold and the second pixel value. The processor increases dynamic range of the recorded image by applying an inverse of the function to the pixel value of the region.

Abstract: Implementations provide for automated detection of a calibration object within a recorded image. In some implementations, a system receives an original image from a camera, wherein the original image includes at least a portion of a calibration chart. The system further derives a working image from the original image. The system further determines regions in the working image, wherein the regions include groups of pixels having values within a predetermined criterion. The system further analyzes two or more of the regions to identify a candidate calibration chart in the working image. The system further identifies at least one region within the candidate calibration chart as a patch, where the identifying of the at least one region is based on a color of the patch. The system further predicts a location of one or more additional patches based on at least the identified patch.

Abstract: A method for generating one or more visual representations of an object colliding with an interface between a simulated fluid and a material. The method includes obtaining shape and movement data of a bulk fluid and an object, identifying an interface where the bulk fluid covers a portion of the object, generating an emitted fluid at the interface, generating shape and movement data of the emitted fluid interacting with the object.

Abstract: An animation system wherein a machine learning model is adopted to generate animated facial actions based on parameters obtained from a live actor. Specifically, the anatomical structure such as a facial muscle topology and a skull surface topology that are specific to the live actor may be used. A skull surface that is specific to a live actor based on facial scans of the live actor and generic tissue depth data. For example, the facial scans of the live actor may provide a skin surface topology of the live actor, based on which the skull surface underneath the skin surface can be derived by “offsetting” the skin surface with corresponding soft tissue depth at different sampled points on the skin surface.

Abstract: A processor performing postprocessing obtains an input image containing both bright and dark regions. The processor obtains a threshold between a first pixel value of the virtual production display and a second pixel value of the virtual production display. The processor modifies the region according to predetermined steps producing a pattern unlikely to occur within the input image, where the pattern corresponds to a difference between the original pixel value and the threshold. The processor can replace the region of the input image with the pattern to obtain a modified image. The virtual production display can present the modified image. A processor performing postprocessing detects the pattern within the modified image displayed on the virtual production display. The processor calculates the original pixel value of the region by reversing the predetermined steps. The processor replaces the pattern in the modified image with the original pixel value.

Abstract: A processor obtains an input image containing both bright and dark regions. The processor obtains a threshold between a first pixel value and a second pixel value of the display. Upon detecting a region of the input image having an original pixel value above the threshold, the processor can create a data structure including a location of the region in the input image and an original pixel value of the region. The data structure occupies less memory than the input image. The display presents the input image including the region of the image having the original pixel value above the threshold. The processor sends the data structure to a camera, which records the presented image. The processor performing postprocessing obtains the data structure and the recorded image and increases dynamic range of the recorded image by modifying the recorded image based on the data structure.

Abstract: A processor obtains an input image containing both bright and dark regions. The processor obtains a threshold between a first pixel value and a second pixel value of the display. Upon detecting a region of the input image having an original pixel value above the threshold, the processor can create a data structure including a location of the region in the input image and an original pixel value of the region. The data structure occupies less memory than the input image. The display presents the input image including the region of the image having the original pixel value above the threshold. The processor sends the data structure to a camera, which records the presented image. The processor performing postprocessing obtains the data structure and the recorded image and increases dynamic range of the recorded image by modifying the recorded image based on the data structure.

Abstract: Embodiments described herein provide an approach of animating a character face of an artificial character based on facial poses performed by a live actor. Geometric characteristics of the facial surface corresponding to each facial pose performed the live actor may be learnt by a machine learning system, which in turn build a mesh of a facial rig of an array of controllable elements applicable on a character face of an artificial character.

Abstract: An animation system is provided for generating an animation control rig for character development, configured to manipulate a skeleton of an animated character. Hierarchical representation of puppets includes groups of functions related in a hierarchy according to character specialization for creating the animated rig are derived using base functions of a core component node. The hierarchical nodes may include an archetype node, at least one appendage node, and at least one feature node. In some implementations, portions of a hierarchical node, including the functions from the core component node, may be shared to generate different animation rigs for a variety of characters. In some implementations, portions of a hierarchical node, including the component node functions, may be reused to build similar appendages of a same animation rig.

Abstract: Compositing is provided in which visual elements from different sources, including live action objects and computer graphic (CG) merged in a constant feed. Representative output images are produced during a live action shoot. The compositing system uses supplementary data, such as depth data of the live action objects for integration with CG items and light marker detection data for device calibration and performance capture. Varying capture times (e.g., exposure times) and processing times are tracked to align with corresponding incoming images and data.