Abstract: A target cell marking method, including: determining an original image format of the original scanned image, and converting the original scanned image into a first image in a preset image format; segmenting the first image into a plurality of image blocks and recording arrangement positions of the image blocks in the first image; respectively inputting the image blocks into a preset deep learning detection model to obtain first position information of target cells in the image blocks; determining second position information of the target cells in the first image according to the first position information and the corresponding arrangement positions; integrating the image blocks according to the arrangement positions to obtain a second image, and marking the target cells in the second image; and converting the second image marked by the target cells into a third image in the original image format, and displaying the third image.

Abstract: Compression techniques by pre-sorting transactions in a consistent way. In at least one embodiment, the compression does not rely on consistent mempool across full nodes. Transactions in a block can be hashed and sorted. Ambiguity can arise from the hashes, which can be resolved using various techniques.

Abstract: Systems and methods to implement a blockchain sharding architecture that running multiple homogeneous chain in parallel to subdivide the workload of the entire network without requiring a centralized coordinator.

Abstract: The present disclosure relates to a holographic projection device, a holographic projection method, and a holographic projection apparatus. The holographic projection device includes a first stereoscopic imaging device including a plurality of transparent pixel blocks; and a light emitting device including a plurality of light emitting units, wherein the plurality of transparent pixel blocks have a one-to-one correspondence with the plurality of light emitting units, and wherein for a light emitting unit A of the plurality of light emitting units, the light emitting unit A is configured to illuminate a transparent pixel block A, and the transparent pixel block A is a transparent pixel block corresponding to the light emitting unit A in the plurality of transparent pixel blocks.

Abstract: A target cell marking method, including: determining an original image format of the original scanned image, and converting the original scanned image into a first image in a preset image format; segmenting the first image into a plurality of image blocks and recording arrangement positions of the image blocks in the first image; respectively inputting the image blocks into a preset deep learning detection model to obtain first position information of target cells in the image blocks; determining second position information of the target cells in the first image according to the first position information and the corresponding arrangement positions; integrating the image blocks according to the arrangement positions to obtain a second image, and marking the target cells in the second image; and converting the second image marked by the target cells into a third image in the original image format, and displaying the third image.

Abstract: Systems and methods to implement a blockchain sharding architecture that running multiple homogeneous chain in parallel to subdivide the workload of the entire network without requiring a centralized coordinator.

Abstract: The present disclosure relates to a holographic projection device, a holographic projection method, and a holographic projection apparatus. The holographic projection device includes a first stereoscopic imaging device including a plurality of transparent pixel blocks; and a light emitting device including a plurality of light emitting units, wherein the plurality of transparent pixel blocks have a one-to-one correspondence with the plurality of light emitting units, and wherein for a light emitting unit A of the plurality of light emitting units, the light emitting unit A is configured to illuminate a transparent pixel block A, and the transparent pixel block A is a transparent pixel block corresponding to the light emitting unit A in the plurality of transparent pixel blocks.

Abstract: Some implementations disclosed herein provide techniques and arrangements to render global light transport in real-time or near real-time. For example, in a pre-computation stage, a first computing device may render points of surfaces (e.g., using multiple light bounces and the like). Attributes for each of the points may be determined. A plurality of machine learning algorithms may be trained using particular attributes from the attributes. For example, a first machine learning algorithm may be trained using a first portion of the attributes and a second machine learning algorithm may be trained using a second portion of the attributes. The trained machine learning algorithms may be used by a second computing device to render components (e.g., diffuse and specular components) of indirect shading in real-time.

Abstract: A “Natural Motion Controller” identifies various motions of one or more parts of a user's body to interact with electronic devices, thereby enabling various natural user interface (NUI) scenarios. The Natural Motion Controller constructs composite motion recognition windows by concatenating an adjustable number of sequential periods of inertial sensor data received from a plurality of separate sets of inertial sensors. Each of these separate sets of inertial sensors are coupled to, or otherwise provide sensor data relating to, a separate user worn, carried, or held mobile computing device. Each composite motion recognition window is then passed to a motion recognition model trained by one or more machine-based deep learning processes. This motion recognition model is then applied to the composite motion recognition windows to identify a sequence of one or more predefined motions. Identified motions are then used as the basis for triggering execution of one or more application commands.

Abstract: Described is a search technology in which spatially varying anisotropic reflectance is modeled using image data captured from a single view. Reflectance at each point is represented using a microfacet-based Bidirectional Reflectance Distribution Function (BRDF). Modeling processes the image data, which provides a partial normal distribution function (NDF) for each surface point. The NDF at each selected point is completed by texture synthesis using similar, overlapping partial NDFs from other points. Also described is a scanning device that illuminates a sample surface from a two-dimensional set of light directions using a linear array of LEDs moved over a flat sample.

Abstract: Some implementations disclosed herein provide techniques and arrangements to render global light transport in real-time or near real-time. For example, in a pre-computation stage, a first computing device may render points of surfaces (e.g., using multiple light bounces and the like). Attributes for each of the points may be determined. A plurality of machine learning algorithms may be trained using particular attributes from the attributes. For example, a first machine learning algorithm may be trained using a first portion of the attributes and a second machine learning algorithm may be trained using a second portion of the attributes. The trained machine learning algorithms may be used by a second computing device to render components (e.g., diffuse and specular components) of indirect shading in real-time.

Abstract: Some implementations disclosed herein provide techniques and arrangements to render global light transport in real-time or near real-time. For example, in a pre-computation stage, a first computing device may render points of surfaces (e.g., using multiple light bounces and the like). Attributes for each of the points may be determined. A plurality of machine learning algorithms may be trained using particular attributes from the attributes. For example, a first machine learning algorithm may be trained using a first portion of the attributes and a second machine learning algorithm may be trained using a second portion of the attributes. The trained machine learning algorithms may be used by a second computing device to render components (e.g., diffuse and specular components) of indirect shading in real-time.

Abstract: A system for reflectance acquisition of a target includes a light source, an image capture device, and a reflectance reference chart. The reflectance reference chart is fixed relative to the target. The light source provides a uniform band of light across at least a dimension of the target. The image capture device is configured and positioned to encompass at least a portion of the target and at least a portion of the reflectance reference chart within a field-of-view of the image capture device. The image capture device captures a sequence of images of the target and the reflectance reference chart during a scan thereof. Reflectance responses are calculated for the pixels in the sequence of images. Reference reflectance response distribution functions are matched to the calculated reflectance responses, and an image of the target is reconstructed based at least in part on the matched reference reflectance response distribution functions.

Abstract: An exemplary method includes providing image data for an illuminated physical sample of a heterogeneous translucent material, determining one or more material properties of the material based in part on a diffusion equation where one of the material properties is a diffusion coefficient for diffusion of radiation in the material and where the determining includes a regularization term for the diffusion coefficient, mapping the one or more material properties to a virtual object volume, assigning virtual illumination conditions to the virtual object volume, and rendering the virtual object volume using the virtual illumination conditions as a boundary condition for a system of diffusion equations of the virtual object volume. Other methods, devices and systems are also disclosed.

Abstract: The method comprises, for each cross-section image, determining the position of the object (O) in relation to the cross-section plane at the moment the cross-section image is captured, and determining a three-dimensional representation (V) of the object (O) using cross-section images (X0 . . . Xm) and positions of the object (O) in relation to the cross-section plane at each moment of image capture. The positions of the object (O) in relation to the cross-section plane are determined using the cross-section images (X0 . . . Xm).

Abstract: Some implementations disclosed herein provide techniques and arrangements to render global light transport in real-time or near real-time. For example, in a pre-computation stage, a first computing device may render points of surfaces (e.g., using multiple light bounces and the like). Attributes for each of the points may be determined. A plurality of machine learning algorithms may be trained using particular attributes from the attributes. For example, a first machine learning algorithm may be trained using a first portion of the attributes and a second machine learning algorithm may be trained using a second portion of the attributes. The trained machine learning algorithms may be used by a second computing device to render components (e.g., diffuse and specular components) of indirect shading in real-time.

Abstract: A mechanism is disclosed for capturing reflected rays from a surface. A first and second lens aligned along a same optical center axis are configured so that a beam of light collimated parallel to the lens center axis directed to a first side, is converged toward the lens center axis on a second side. A first light beam source between the first and second lenses directs a light beam toward the first lens parallel to the optical center axis. Second light beam source(s) on the second side of the first lens, direct a light beam toward a focal plane of the first lens at a desired angle. An image capturing component, at the second side of the second lens, has an image capture surface directed toward the second lens to capture images of the light reflected from a sample capture surface at the focal plane of the first lens.

Abstract: The method of the invention includes: determining a set of points of a space and a value of each of these points at a given moment, the set of points including the points of the object in the position thereof at the given moment; selecting a three-dimensional representation function that can be parameterized with parameters and an operation that gives, using the three-dimensional representation function, a function for estimating the value of each point in the space; and determining parameters, such that, for each point in the set, the estimation of the value of the point substantially gives the value of the point.

Abstract: A system for reflectance acquisition of a target includes a light source, an image capture device, and a reflectance reference chart. The reflectance reference chart is fixed relative to the target. The light source provides a uniform band of light across at least a dimension of the target. The image capture device is configured and positioned to encompass at least a portion of the target and at least a portion of the reflectance reference chart within a field-of-view of the image capture device. The image capture device captures a sequence of images of the target and the reflectance reference chart during a scan thereof. Reflectance responses are calculated for the pixels in the sequence of images. Reference reflectance response distribution functions are matched to the calculated reflectance responses, and an image of the target is reconstructed based at least in part on the matched reference reflectance response distribution functions.

Abstract: A “Scene Re-Lighter” provides various techniques for using an automatically reconstructed light transport matrix derived from a sparse sampling of images to provide various combinations of complex light transport effects in images, including caustics, complex occlusions, inter-reflections, subsurface scattering, etc. More specifically, the Scene Re-Lighter reconstructs the light transport matrix from a relatively small number of acquired images using a “Kernel Nyström” based technique adapted for low rank matrices constructed from sparsely sampled images. A “light transport kernel” is incorporated into the Nyström method to exploit nonlinear coherence in the light transport matrix. Further, an adaptive process is used to efficiently capture the sparsely sampled images from a scene. The Scene Re-Lighter is capable of achieving good reconstruction of the light transport matrix with only few hundred images to produce high quality relighting results.