Abstract: The invention discloses a MIMO different-factor partial-form model-free control method with parameter self-tuning. In view of the limitations of the existing MIMO partial-form model-free control method with the same-factor structure, namely, at time k, different control inputs in the control input vector can only use the same values of penalty factor and step-size factors, the invention proposes a MIMO partial-form model-free control method with the different-factor structure, namely, at time k, different control inputs in the control input vector can use different values of penalty factors and/or step-size factors, which can solve control problems of strongly nonlinear MIMO systems with different characteristics between control channels widely existing in complex plants. Meanwhile, parameter self-tuning is proposed to effectively address the problem of time-consuming and cost-consuming when tuning the penalty factors and/or step-size factors.

Abstract: A parking assistance device includes an overhead image generation unit generating an overhead image from a captured image obtained by capturing an image around a towing vehicle, a towing determination unit determining whether a towed vehicle is towed, an overhead image display range setting unit selecting a trimming range from a plurality of display ranges at least including a first display range and a second display range wider than the first display range, and a display image generation unit generating an overhead image for display by trimming the trimming range of the overhead image, and a display image including the overhead image for display on which the towing vehicle is superimposed. The overhead image display range setting unit selects the first display range when the towing vehicle does not tow the towed vehicle, and selects the second display range when the towing vehicle tows the towed vehicle.

Abstract: Methods and apparatus relating to techniques for provision of low power foveated rendering to save power on GPU (Graphics Processing Unit) and/or display are described. In various embodiment, brightness/contrast, color intensity, and/or compression ratio applied to pixels in a fovea region are different than those applied in regions surrounding the fovea region. Other embodiments are also disclosed and claimed.

Abstract: Example implementations relate to emulating 3D texture patterns in a printer system. One example implementation determines a 3D texture pattern data having a number of pattern pixels at different heights and associated with respective surfaces of a corresponding 3D texture pattern. Luminance change data is determined for each pattern pixel depending on an angle between a normal vector of the respective surface and a simulated light vector. Image data is obtained having a number of image pixels and the luminance of each image pixel is adjusted depending on the luminance change data of a corresponding pattern pixel in order to generate an image with an emulated 3D texture pattern.

Abstract: Systems, computer program products, and methods are described herein for implementing steganography based augmented reality platform. The present invention is configured to provide an augmented reality application for installation on a computing device of a user; receive, via the augmented reality application, a real-time visual feed, wherein the real-time visual feed comprises an image, wherein the image comprises a message that is steganographically embedded therein; determine that the computing device of the user is authorized to access the message embedded in the image in the visual feed; and generate an acknowledgement that the computing device of the user is authorized to access the message embedded in the image in the visual feed; and transmit control signals configured to cause the computing device of the user to overlay, via the augmented reality application, the acknowledgement in a vicinity of the image in the real-time visual feed.

Abstract: A mechanism is described for facilitating slimming of neural networks in machine learning environments. A method of embodiments, as described herein, includes learning a first neural network associated with machine learning processes to be performed by a processor of a computing device, where learning includes analyzing a plurality of channels associated with one or more layers of the first neural network. The method may further include computing a plurality of scaling factors to be associated with the plurality of channels such that each channel is assigned a scaling factor, wherein each scaling factor to indicate relevance of a corresponding channel within the first neural network. The method may further include pruning the first neural network into a second neural network by removing one or more channels of the plurality of channels having low relevance as indicated by one or more scaling factors of the plurality of scaling factors assigned to the one or more channels.

Abstract: A mixed reality device (30) employing a mixed reality display (40) for visualizing a virtual augmentation of a physical anatomical model, and a mixed reality controller (50) for controlling a visualization by the mixed reality display (40) of the virtual augmentation of the physical anatomical model including a mixed reality interaction between the physical anatomical model and a virtual anatomical model. The mixed reality controller (50) may employ a mixed reality registration module (51) for controlling a spatial registration between the physical anatomical model within a physical space and the virtual anatomical model within a virtual space, and a mixed reality interaction module for controlling the mixed reality interaction between the physical anatomical model and the virtual anatomical model based on the spatial registration between the physical anatomical model within the physical space and the virtual anatomical model within the virtual space.

Abstract: Some implementations relate to methods, systems, and computer-readable media to generate 3D assets from 2D images. In some implementations, a computer-implemented method to generate a 3D asset for an object using a trained machine learning model includes providing a 2D image of the object as input to the trained machine learning model, obtaining a template 3D mesh and a representative of a class of objects of interest that includes the object, generating based on the template 3D mesh and the representative of the class, a rigged 3D mesh for the object, deforming and posing the rigged 3D mesh to match the 2D image, and applying a texture extracted from the 2D image to the deformed and posed 3D mesh to create the 3D asset of the object.

Abstract: Graphic arts software has evolved to provide users with a variety of mark making tools to simulate different brushes, papers, and applied media such as ink, chalk, watercolour, spray paint and oils. However, in many instances the marks rendered appear unnatural and artificial despite the software's goal being to simulate as realistically. Accordingly, it would be beneficial to provide either users or the software application with a mechanism to remove or reduce artifacts indicative of artificial generation, e.g. rapid transitions. Further, in many instances the graphic images generated and/or manipulated refer to imagined environments or have elements that are physical in nature. Accordingly, it would be beneficial to provide users with a range of mark making tools that represent marks made by mark making tools comprising multiple elements following physical laws.

Abstract: Systems and methods for graph total variation (GTV) based reconstruction of electrical potentials on a cardiac surface are disclosed. GTV-based systems and methods incorporate information about the graph structure of the heart surface as well as imposing sparsity constraints on neighboring nodes. To this end, the present disclosure uses a novel way of calculating derivatives on irregular meshes, and provides a fast solver to compute an inverse solution more efficiently than in previous systems and methods. Moreover, fast-changing signals can be recovered with less smoothing and thus greater fidelity to the original signals.

Abstract: Approaches are presented for training an inverse graphics network. An image synthesis network can generate training data for an inverse graphics network. In turn, the inverse graphics network can teach the synthesis network about the physical three-dimensional (3D) controls. Such an approach can provide for accurate 3D reconstruction of objects from 2D images using the trained inverse graphics network, while requiring little annotation of the provided training data. Such an approach can extract and disentangle 3D knowledge learned by generative models by utilizing differentiable renderers, enabling a disentangled generative model to function as a controllable 3D “neural renderer,” complementing traditional graphics renderers.

Abstract: A recording medium recording an appearance frequency calculation program for causing an information processing apparatus to execute processing includes: construction processing of constructing thread groups each including threads; acquisition processing in which the thread group acquires a data group including a same number of pieces of data as a number of threads constituting the thread group, each thread being responsible for one piece of data of the data group; and addition processing in which the thread adds one to a first storage area that stores an appearance frequency of a first numerical value, and a duplication number indicating a number of duplication is added to the first storage area when the own thread is a representative thread that is present alone in the thread group that is responsible for the data of the first numerical value when the first numerical value is duplicated in the data group.

Abstract: A crowd-sourced modeling system to perform operations that include: receiving image data that comprises image attributes; accessing a 3D model based on at least the image attributes of the image data, wherein the 3D model comprises a plurality of parts that collectively depict an object or environment; identifying a change in the object or environment based on a comparison of the image data with the plurality of parts of the 3D model, the change corresponding to a part of the 3D model from among the plurality of parts; and generating an update to the part of the 3D model based on the image attributes of the image data.

Abstract: A method includes receiving (i) a modeled surface of at least a portion of a heart and (ii) multiple EP values measured at multiple respective positions in the heart. Multiple regions are defined on the modeled surface and, for each region, a confidence level is estimated for the EP values whose positions fall in the region. The modeled surface is presented to a user, including (i) the EP values overlaid on the modeled surface, and (ii) the confidence level graphically visualized in each region of the modeled surface.

Abstract: There is provided an information processing apparatus and an information processing method that can enhance the image quality while, at the same time, reducing increase in client's throughput. Image data of a plurality of projection directions is generated by projecting 3D data in a plurality of projection directions and converting the 3D data into two-dimensional data, and projection direction information indicating the projection direction of each piece of the image data is generated as projection metadata. Further, the projection direction information includes additional projection direction identification information that indicates that the image data has been generated by projection in additional projection directions. The present technology is applicable, for example, to a data generation apparatus that generates data for delivering a point cloud.

Abstract: An apparatus generates truly random numbers. The apparatus includes a container that is at least partially filled with a fluid (e.g., water or air). The apparatus also includes objects (e.g., dice) suspended freely in the fluid. The apparatus includes agitators configured to stir the fluid, and cameras configured to capture images of the objects. When the agitators stir the fluid, the objects move freely (e.g., move with the created currents) in the fluid in the container. The apparatus also includes a random number generation circuit coupled to the cameras. The random number generation circuit is configured to generate random numbers based on the images captured by the cameras.

Abstract: The disclosed artificial reality system can provide a user self representation in an artificial reality environment based on a self portion from an image of the user. The artificial reality system can generate the self representation by applying a machine learning model to classify the self portion of the image. The machine learning model can be trained to identify self portions in images based on a set of training images, with portions tagged as either depicting a user from a self-perspective or not. The artificial reality system can display the self portion as a self representation in the artificial reality environment by positioning them in the artificial reality environment relative to the user's perspective in the artificial reality environment. The artificial reality system can also identify movements of the user and can adjust the self representation to match the user's movement, providing more accurate self representations.

Abstract: Embodiments described herein include an expressive icon system to present an animated graphical icon, wherein the animated graphical icon is generated by capture facial tracking data at a client device. In some embodiments, the system may track and capture facial tracking data of a user via a camera associated with a client device (e.g., a front facing camera, or a paired camera), and process the facial tracking data to animate a graphical icon.

Abstract: Systems, methods, devices, and non-transitory media of the various embodiments may provide for extrapolating a breakline for a user in a graphical application, such as an Earthworks rendering application. Various embodiments may enable a breakline to be extrapolated and rendered on a surface from two or more points selected by a user on that surface. In various embodiments, the surface may be any type directional surface, such as a triangle mesh, pointcloud, heightmap, fusions of such surfaces, etc.

Abstract: A system, method, and chip, which may be used for attaching digital reality applications to and enabling interactions with dynamic objects in a virtual world. The system comprises a server comprising a persistent virtual world system storing virtual replicas of static and dynamic real world objects. A client device connected to the server via a network enables interaction with one or more digital reality applications virtually attached to dynamic objects of the real world. Chips installed on dynamic objects of the real world store dynamic object data comprising at least geo-location data of the host dynamic objects. Combining static object data stored in the server and the dynamic object data generates a persistent virtual world system that can be streamed to the client device for interaction with users while accurately tracking the dynamic objects and client devices.