Various embodiments set forth techniques for positioning speakers within a venue. The techniques include generating, via a machine learning model, at least one of a two-dimensional (2D) representation or a three-dimensional (3D) representation of a venue based on one or more images of the venue. The techniques further include determining one or more parameters associated with one or more speakers to be placed within the venue based on the at least one of the 2D representation or the 3D representation.

6Examples described herein provide a method that includes obtaining, by a processing device, three-dimensional (3D) voxel data. The method further includes performing, by the processing device, gray value thresholding based at least in part on the 3D voxel data and assigning a classification value to at least one voxel of the 3D voxel data. The method further includes defining, by the processing device, segments based on the classification value. The method further includes filtering, by the processing device, the segments based on the classification value. The method further includes evaluating, by the processing device, the segments to identify a surface voxel per segment. The method further includes determining, by the processing device, a position of a surface point within the surface voxel.

A method for generating three-dimensional (3D) content for a performance of a performer in an apparatus for generating 3D content is provided. The apparatus for generating 3D content obtains a 3D appearance model and texture information of the performer using the images of the performer located in the space, sets a plurality of nodes in the 3D appearance model of the performer, generates a 3D elastic model of the performer using the texture information, obtains a plurality of first images of the performance scene of the performer photographed by a plurality of first cameras installed in a performance hall, renders a plurality of virtual images obtained by photographing a 3D appearance model according to position change of each node in a 3D elastic model of the performer through a plurality of first virtual cameras having the same intrinsic and extrinsic parameters as the plurality of first cameras, using the texture information, determines an optimal position of each node by using color differences between the plurality of first images and a plurality of first rendered with respect to the plurality of virtual images obtained by the plurality of first virtual cameras, and generates a mesh model describing the performance scene by applying 3D elastic model parameter values corresponding to the optimal position of each node to the 3D elastic model.

Methods and systems for manufacturing an orthodontic appliance with an object incorporated in a surface thereof comprising: acquiring a preliminary appliance 3D digital model; acquiring an object 3D digital model; obtaining a desired coupling location of the object on the orthodontic appliance; positioning the object 3D digital model onto a surface of the preliminary appliance 3D digital model based on the obtained coupling location; causing an initial predetermined degree of penetration; merging the object 3D digital model with the preliminary appliance 3D digital model to generate an appliance 3D digital model of the orthodontic appliance with the object incorporated in the surface; and storing the appliance 3D digital model in an internal memory of the electronic device.

This application discloses methods, systems, and computer-implemented virtualization software applications and computer-implemented graphical user interface tools for remote virtual visualization of structures. Images are captured by an imaging vehicle of a structure and the captured images are transmitted to a remote server via a communication network. Using virtual 3D digital modeling software the server, using the images received from the imaging vehicle, generates a virtual 3D digital model of the structure and stores it in a database. This virtual 3D digital model can be accessed by remote users, using virtualization software applications, and used to view images of the structure. The user is able to manipulate the images and to view them from various perspectives and compare the before-the-damage images with images taken after damage have occurred. Based on all this the user is enabled to remotely communicate with an insurance agent and/or file an insurance claim.

Technologies for 3D virtual environment placement of 3D models based on 2D images are disclosed. At least an outline of a 3D virtual environment may be generated. A 2D image of one or more 2D images may be identified. A first product from the first 2D image may be identified. At least one 3D model of one or more 3D models based, at least, on the first product may be determined. A first location for placement of the first product in the 3D virtual environment may be identified. The at least one 3D model may be added within the 3D virtual environment based, at least, on the first location. The 3D virtual environment may be rendered into a visually interpretable form. A second product may be identified from the first 2D image, forming a first grouping of products. A starting element for the first grouping of products may be determined.

Implementations described and claimed herein provide systems and methods for object modeling. In one implementation, input imagery of a real-world object is obtained at an object modeling system. The input imagery is captured using an imaging system from a designated viewing angle. A 3D model of the real-world object is generated based on the input imagery using the object modeling system. The 3D model is generated based on a plurality of stages corresponding to a sequence of polygons stacked in a direction corresponding to the designated viewing angle. The 3D model is output for presentation using a presentation system.

A method for conducting a three dimensional (3D) video conference between multiple participants, the method may include determining, for each participant and multiple times during the 3D video conference, updated 3D participant representation information within the virtual 3D video conference environment; and generating, for at least one participant and multiple times during the 3D video conference, an updated representation of a virtual 3D video conference environment, the updated representation of virtual 3D video conference environment represents the updated 3D participant representation information for at least some of the multiple participants; and wherein the 3D participant representation information comprises a 3D model and one or more texture maps.

Disclosed are techniques for processing image data. In some aspects, a three-dimensional model can be determined corresponding to an object in an input image. Based on the three-dimensional model, an estimated focal length can be determined that corresponds to the input image. An estimated depth associated with the object in the input image can be calculated based on the estimated focal length and an input image focal length.

Embodiments disclosed herein generally relate to predicting geographic-atrophy lesion growth and/or geographic atrophy lesion size in an eye. The predictions can be generated by processing a data object using a neural network. The data object may include a three-dimensional data object representing a depiction of at least part of the eye or a multi-channel data object representing one or more decorresponding pictions of at least part of the eye. The neural network can include a convolutional multi-task neural network that is trained to learn features that are predictive of both lesion-growth and lesion-size outputs.