Patents Assigned to Pixar
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Patent number: 10347042Abstract: Techniques are disclosed for generating quality renderings of volumes by sampling a volume light by generating and analyzing a sparse voxel octree. In one embodiment, a volumetric light source may be divided into voxels and importance information stored in an octree. An importance value may be determined for each voxel based on the amount of emitted light in the region associated with that voxel. Importance values regarding the individual voxels may be stored in the leaves of the octree. Each interior node may be associated with an importance value equal to the sum of the importance values of its children. The root node may be associated with the total importance of the entire octree.Type: GrantFiled: March 13, 2014Date of Patent: July 9, 2019Assignee: PixarInventor: Florian Hecht
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Patent number: 10338761Abstract: User interface display layouts are provided that draw a user's attention to a specific element or elements by de-emphasizing the surrounding content, but without removing the de-emphasized content from the interface. This ability to maintain the whole presentable layout with visibility layers and without layout changes provides a useful navigation experience for the user as it is clear where the user's attention should go and yet the surrounding content is still subtly there, constantly reminding the user of the other available content. De-emphasis of certain content items is achieved by modifying display characteristics of those content items relative to a base display level, for example by lowering saturation, lowering opacity, and/or de-focusing (as if the user is looking through a camera) and modification can be done variably. Driven by a relevancy score, each content item in a display layout can be de-emphasized more or less depending on which content is more meaningful to the user's filtering actions.Type: GrantFiled: April 8, 2011Date of Patent: July 2, 2019Assignee: PIXARInventors: Yasmin Khan, Maxwell E. Planck, Najeeb Tarazi, Michael Kass
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Patent number: 10319133Abstract: Users may dynamically specify a “posing root” node in an animation hierarchy that is different than the model root node used to define the animation hierarchy. When a posing root node is specified, users specify the pose, including translations and rotations, of other nodes relative to the posing root node, rather than the model root node. Poses of nodes may be specified using animation variable values relative to the posing root node. Animation variable values specified relative to the posing root node are dynamically converted to equivalent animation variable values relative to the model root node, which then may be used to pose an associated model. Animation data may be presented to users relative to the current posing root node. If a posing root node is changed to a different location, the animation data is converted so that it is expressed relative to the new posing root node.Type: GrantFiled: November 13, 2011Date of Patent: June 11, 2019Assignee: PixarInventors: Kurt Fleischer, Warren Trezevant, Andrew Witkin
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Patent number: 10311552Abstract: The present disclosure relates to using a neural network to efficiently denoise images that were generated by a ray tracer. The neural network can be trained using noisy images generated with noisy samples and corresponding denoised or high-sampled images (e.g., many random samples). An input feature to the neural network can include color from pixels of an image. Other input features to the neural network, which would not be known in normal image processing, can include shading normal, depth, albedo, and other characteristics available from a computer-generated scene. After the neural network is trained, a noisy image that the neural network has not seen before can have noise removed without needing manual intervention.Type: GrantFiled: June 22, 2017Date of Patent: June 4, 2019Assignee: PixarInventors: Mark Meyer, Anthony DeRose, Steve Bako
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Patent number: 10297053Abstract: Provided herein are methods, systems, and computer products for evaluating nodes concurrently using a modified data flow graph. The modified data flow graph can identify independent nodes that can run as separate tasks. However, rather than relying on declared dependencies, embodiments herein can determine dependencies between segments of data elements in a data flow graph, and modify the data flow graph to take advantage of the determined dependencies. In such embodiments, the data elements can be divided into segments. By separating data elements into segments, nodes that previously depended on each other can be evaluated concurrently when independent segments are identified.Type: GrantFiled: May 10, 2016Date of Patent: May 21, 2019Assignee: PixarInventors: Florian Zitzelsberger, George ElKoura
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Patent number: 10282885Abstract: A multi-scale method is provided for computer graphic simulation of incompressible gases in three-dimensions with resolution variation suitable for perspective cameras and regions of importance. The dynamics is derived from the vorticity equation. Lagrangian particles are created, modified and deleted in a manner that handles advection with buoyancy and viscosity. Boundaries and deformable object collisions are modeled with the source and doublet panel method. The acceleration structure is based on the fast multipole method (FMM), but with a varying size to account for non-uniform sampling.Type: GrantFiled: December 29, 2017Date of Patent: May 7, 2019Assignee: PixarInventor: Alexis Angelidis
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Patent number: 10264046Abstract: Techniques are proposed for embedding transition points in media content. A transition point system retrieves a time marker associated with a point of interest in the media content. The transition point system identifies a first position within the media content corresponding to the point of interest. The transition point system embeds data associated with the time marker into the media content at a second position that is no later in time than the first position. The transition point system causes a client media player to transition from a first image quality level to a second quality level based on the time marker.Type: GrantFiled: June 28, 2017Date of Patent: April 16, 2019Assignee: PixarInventor: Dominic Glynn
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Publication number: 20190108298Abstract: Provided are methods, systems, and computer-program products for recovering from intersections during a simulation of an animated scene when a collision detection operation is active. For example, the collision detection operation can be selectively activated and deactivated during the simulation of one or more objects for a time step based on an intersection analysis, which can identify intersections of the one or more objects for the time step. Once the collision detection operation is deactivated, a collision response can apply one or more forces to intersecting portions of the one or more objects to eliminate the intersections of the one or more objects. For example, a portion of a cloth that is in a state of intersection can be configured such that the collision detection operation is not performed on the portion, thereby allowing the cloth to be removed from inside of another object by a collision response algorithm.Type: ApplicationFiled: October 6, 2017Publication date: April 11, 2019Applicant: PIXARInventor: David Eberle
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Patent number: 10192342Abstract: Systems and methods can provide computer animation of animated scenes or interactive graphics sessions. A grid camera separate from the render camera can be created for segments where the configurations (actual or predicted) of the render camera satisfy certain properties, e.g., an amount of change is within a threshold. If a segment is eligible for the use of the separate grid camera, configurations of the grid camera during a segment can be determined, e.g., from the configurations of the render camera. The configurations of the grid camera can then be used to determine grids for rendering objects. If a segment is not eligible for the use of the grid camera, then the configurations of the render camera can be used to determine the grids for rendering.Type: GrantFiled: November 4, 2016Date of Patent: January 29, 2019Assignee: PixarInventors: Alexander Kolliopoulos, Brandon Kerr
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Patent number: 10192346Abstract: This disclosure provides an approach for automatically generating UV maps for modified three-dimensional (3D) virtual geometry. In one embodiment, a UV generating application may receive original 3D geometry and associated UV panels, as well as modified 3D geometry created by deforming the original 3D geometry. The UV generating application then extracts principal stretches of a mapping between the original 3D geometry and the associated UV panels and transfers the principal stretches, or a function thereof, to a new UV mapping for the modified 3D geometry. Transferring the principal stretches or the function thereof may include iteratively performing the following steps: determining new UV points assuming a fixed affine transformation, determining principal stretches of a transformation between the modified 3D geometry and the determined UV points, and determining a correction of a transformation matrix for each triangle to make the matrix a root of a scoring function.Type: GrantFiled: September 28, 2016Date of Patent: January 29, 2019Assignee: PixarInventors: Fernando Ferrari De Goes, Mark Meyer
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Patent number: 10180714Abstract: A user interface provides for multi-stroke marking menus and other uses, for use on multitouch devices. One variant of multi-stroke marking is where users draw strokes with either both hands simultaneously or alternating between the hands. Alternating strokes between hands doubles the number of accessible menu items for the same number of strokes. Other inputs can be used as well, such as timing, placement, and direction.Type: GrantFiled: September 17, 2010Date of Patent: January 15, 2019Assignee: PixarInventors: Kenrick Kin, Maneesh Agrawala
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Patent number: 10169909Abstract: Particular embodiments comprise providing a surface mesh for an object, generating a voxel grid comprising volumetric masks for the mesh, and generating a lit mesh, wherein the lit mesh comprises a shaded version of the mesh as positioned in a scene. The voxel grid may be positioned over the lit mesh in the scene, and a first ray may be traced to a position of the voxel grid. If the traced ray passed through the voxel grid and hit a location on the lit mesh, then one or more second rays may be traced to the hit location on the lit mesh. If the traced ray hit a location in the voxel grid but did not hit a location on the lit mesh, then one or more second rays may be traced from the hit location in the voxel grid to the closest locations on the lit mesh. Finally, color sampled at one or more locations proximate to the position of the voxel grid may be blurred outward through the voxel grid to create a volumetric projection.Type: GrantFiled: February 13, 2015Date of Patent: January 1, 2019Assignee: PixarInventors: Alexis Angelidis, Jacob Porter Merrell, Robert Moyer, Philip Child
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Patent number: 10163243Abstract: Techniques are disclosed for accounting for features of computer-generated dynamic or simulation models being at different scales. Some examples of dynamic or simulation models may include models representing hair, fur, strings, vines, tails, or the like. In various embodiments, features at different scales in a complex dynamic or simulation model can be treated differently when rendered and/or simulated.Type: GrantFiled: July 17, 2015Date of Patent: December 25, 2018Assignee: PixarInventors: Andrew P. Witkin, John Anderson, Lena Petrovic
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Patent number: 10134199Abstract: Techniques for animating a non-rigid object in a computer graphics environment. A three-dimensional (3D) curve rigging element representing the non-rigid object is defined, the 3D curve rigging element comprising a plurality of knot primitives. One or more defined values are received for an animation control attribute of a first knot primitive. One or more values are generated, for a second animation control attribute for a second knot primitive, based on the plurality of animation control attributes of a neighboring knot primitive. An animation is then rendered using the 3D curve rigging element. More specifically, one or more defined values for the first attribute of the first knot primitive and the generated value for the second attributes of the second knot primitive are used to generate the animation. The rendered animation is output for display.Type: GrantFiled: September 30, 2016Date of Patent: November 20, 2018Assignee: PixarInventors: Mark C. Hessler, Jeremie Talbot, Mark Piretti, Kevin A. Singleton
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Publication number: 20180293712Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.Type: ApplicationFiled: April 5, 2018Publication date: October 11, 2018Applicant: PIXARInventors: Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Jan Novak
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Publication number: 20180293710Abstract: The present disclosure relates to using a neural network to efficiently denoise images that were generated by a ray tracer. The neural network can be trained using noisy images generated with noisy samples and corresponding denoised or high-sampled images (e.g., many random samples). An input feature to the neural network can include color from pixels of an image. Other input features to the neural network, which would not be known in normal image processing, can include shading normal, depth, albedo, and other characteristics available from a computer-generated scene. After the neural network is trained, a noisy image that the neural network has not seen before can have noise removed without needing manual intervention.Type: ApplicationFiled: June 22, 2017Publication date: October 11, 2018Applicant: PIXARInventors: Mark Meyer, Anthony DeRose, Steve Bako
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Publication number: 20180293496Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.Type: ApplicationFiled: April 5, 2018Publication date: October 11, 2018Applicant: PIXARInventors: Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Jan Novak
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Publication number: 20180293713Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.Type: ApplicationFiled: April 5, 2018Publication date: October 11, 2018Applicant: PIXARInventors: Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Mark Meyer, Jan Novak
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Patent number: 10062199Abstract: A method and system for rendering a three-dimensional (3D) scene by excluding non-contributing objects are disclosed. A preliminary object analysis using relatively few rays can be performed to determine which off-camera objects are to be excluded or included in the rendering process. The preliminary object analysis may involve performing an initial ray path tracing to identify intersections between a plurality of rays and one or more objects in the 3D scene. The object analysis can include identifying whether a first object in the 3D scene can be identified as an off-camera object. When the first object is identified as an off-camera object, a number of intersections between the plurality of rays and the first object can be counted. If the number of intersections is less than a corresponding threshold, the first object can be identified as being excluded from a future rendering process to render the first frame.Type: GrantFiled: June 27, 2016Date of Patent: August 28, 2018Assignee: PixarInventor: Christopher R. Schoeneman
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Publication number: 20180189999Abstract: A multi-scale method is provided for computer graphic simulation of incompressible gases in three-dimensions with resolution variation suitable for perspective cameras and regions of importance. The dynamics is derived from the vorticity equation. Lagrangian particles are created, modified and deleted in a manner that handles advection with buoyancy and viscosity. Boundaries and deformable object collisions are modeled with the source and doublet panel method. The acceleration structure is based on the fast multipole method (FMM), but with a varying size to account for non-uniform sampling.Type: ApplicationFiled: December 29, 2017Publication date: July 5, 2018Applicant: PIXARInventor: Alexis Angelidis