Abstract: A method for generating a volumetric image of a subject from at least one 2 dimensional image, said at least one 2 dimensional image having a limited number of viewpoints, said volumetric image insertable into an environment.

Abstract: A method for generating metadata to accompany a volumetric video for texels in an object in a volumetric video. The method comprises steps of: inputting a 2D representation of the object; identifying areas in the representation that have the same one or more properties with respect to light; and generating input material groups, where all texels in each input material group have the same properties with respect to light. There exists a correspondence between at least part of the input representation and at least part of the object in the volumetric video, so that there is a correspondence between texels in the representation and texels in the object so that output material groups can be generated from the input material groups and the properties with respect to light can be stored with the volumetric video as metadata.

Abstract: A method and system for improving a three-dimensional (3D) representation of objects using semantic data. The method comprises receiving an input data generated in response to captured video in a filming area; setting at least one parameter for each region in the input data; and generating a 3D representation based in part on the at least one parameter and semantic data associated with the input data.

Abstract: The present invention generally pertains to systems, methods, and non-transitory processor-readable mediums for ensuring a match between geometry and texture when playing volumetric videos in a web browser.

Abstract: System and method for texturing a 3D surface using 2D images sourced from a plurality of imaging devices. System and method for applying a realistic texture to a model, based on texture found in one or more two-dimensional (2D) images of the object, with the texture covering the entire 3D model even if there are portions of the object that were invisible in the 2D image. System and method which does not require machine learning, is not incapable of blending between images, and which is not incapable of filling in portions of a 3D model that are invisible in the 2D image.

Abstract: A computer-implemented method of generating of a database for training a neural network configured for converting 2d images into 3d models comprising steps of: (a) obtaining 3d models; (b) rendering said 3d models in a 2d format from at least one view point; and (c) collecting pairs further comprising said rendered 2d image frame and said corresponding sampled 3d models each.

Abstract: A method and system for improving a three-dimensional (3D) representation of objects using semantic data. The method comprises receiving an input data generated in response to captured video in a filming area; setting at least one parameter for each region in the input data; and generating a 3D representation based in part on the at least one parameter and semantic data associated with the input data.