Provided is a training dataset generating system including: a communicator to receive a two-dimensional (2D) image obtained by photographing a target object; and a controller configured to generate, based on the 2D image and based on three-dimensional (3D) data for the target object, a training dataset comprising a synthetic image and comprising labeling information, wherein the controller is configured to generate the training data set by: generating, based on the 3D data, a rendered image, generating the synthetic image, based on the 2D image and the rendered image, through deep learning training, extracting, based on at least one of the 3D data or the rendered image, the labeling information for the target object, and generating the training dataset.

Natural language processing of a physician's comments regarding a medical image may be executed by artificial intelligence software to determine a state (e.g., normal or abnormal) of various anatomical features (e.g., ligaments, tendons, bones, muscles, etc.). The determined anatomical features and their corresponding states may then be used to select one or more representative medical images from a library of stored images (e.g., illustrations or photographs). This process may be repeated to identify multiple representative medical images for different anatomical features and states, and the multiple medical images may be combined (such as by morphing, overlaying, or otherwise combining the images) to form a composite image that illustrates the specific patient anatomy.

A digital asset management system is enhanced with an end-to-end deep zoom feature functionality that receives a user request to generate a deep zoom image of an asset, performs an image conversion if necessary, generates the deep zoom image and stores corresponding image folders and files in a transient storage separate from assets managed by the digital asset management system, and cleans up the deep zoom files after a pre-configured time period. The deep zoom image is rendered directly from the transient storage without having to involve the repository, which is separately managed by the digital asset management system. A new Web context is created and provided for viewing the deep zoom image within a browser-based user interface of the digital asset management system for a seamless user experience.

Systems and methods for producing an acceleration structure provide for subdividing a 3-D scene into a plurality of volumetric portions, which have different sizes, each being addressable using a multipart address indicating a location and a relative size of each volumetric portion. A stream of primitives is processed by characterizing each according to one or more criteria, selecting a relative size of volumetric portions for use in bounding the primitive, and finding a set of volumetric portions of that relative size which bound the primitive. A primitive ID is stored in each location of a cache associated with each volumetric portion of the set of volumetric portions. A cache location is selected for eviction, responsive to each cache eviction decision made during the processing. An element of an acceleration structure according to the contents of the evicted cache location is generated, responsive to the evicted cache location.

A method for operating a robotic system includes determining a discretized object model representative of a target object; determining a discretized platform model representative of a task location; determining height measures based on real-time sensor data representative of the task location; and dynamically deriving a placement location based on (1) overlapping the discretized object model and the discretized platform model for stacking objects at the task location and (2) calculating a placement score associated with the overlapping based on the height measures.

Systems, methods, and devices for managing media storage and delivery, including obtaining, by a media access function (MAF), a Graphics Language Transmission Format (glTF) file corresponding to a scene; obtaining from the glTF file a uniform resource locator (URL) parameter indicating a binary data blob; determining that the binary data blob has a Concise Binary Object Representation (CBOR) format; converting the binary data blob into an object having a JavaScript Object Notation (JSON) format using a CBOR parser function implemented by the MAF; and obtaining media content corresponding to the scene based on the object.

Systems, methods, and devices for managing media storage and delivery, including obtaining, by a media access function (MAF), a glTF file corresponding to a scene; determining that the glTF file has a CBOR format; converting the glTF file into a converted glTF file having a JSON format using a first CBOR parser function implemented by the MAF; and obtaining media content corresponding to the scene based on the converted glTF file.

An object is to efficiently generate virtual viewpoint images in different image formats. The image generation system includes a plurality of rendering modules. Then, virtual viewpoint information indicating a virtual viewpoint, for generating a virtual viewpoint image adapted to a predetermined image format, is converted into a plurality of pieces of virtual viewpoint information which indicate a plurality of virtual viewpoints, based on performance of a plurality of rendering modules. Then, based on the plurality of pieces of virtual viewpoint information after being converted, contents of rendering that should be executed are allocated to at least part of the plurality of rendering modules. Then, a virtual viewpoint image adapted to the predetermined image format is generated by using results of rendering processing by the at least part of the rendering modules.

System, apparatus, device, method and/or computer program product are disclosed for detecting the authenticity of an image file transferred from a device to a server based on an image authenticity detection configuration determined by a server application. A device application is operated by a device, and a server application is operated by a server. The device application sends, to the server application, user data, device data, or environment data. The server application determines an image authenticity detection configuration to indicate one or more parameters to be used by the device to generate a first image file, and authorized changes to be made to the first image file to generate a second image file. The device application sends the second image file to the server application. The server application detects whether the received second image file contains changes matching authorized changes indicated by the image authenticity detection configuration.

Methods and systems are disclosed for the conversion of a two-dimensional video media into a rendered three-dimensional video media, said conversion commonly being facilitated by at least one database having frames of pre-rendered three-dimensional recreations containing at least one rendered model in at least one location and in at least one pose within a rendered area, and having a means for selecting the pre-rendered three-dimensional frame from the database that most closely resembles the two-dimensional video media. Further embodiments include interactable elements in the rendered three-dimensional video media, said interactable elements displaying information when the interactable element is manipulated by a user.