Systems, methods, and non-transitory computer-readable media can identify a virtual character being presented to a user within a real-time immersive environment. A first animation to be applied to the virtual character is determined. A nonverbal communication animation to be applied to the virtual character simultaneously with the first animation is determined. The virtual character is animated in real-time based on the first animation and the nonverbal communication animation.

Various implementations disclosed herein include devices, systems, and methods that render a reflective surface of a computer-generated reality (“CGR”) object based on synthesis in a CGR environment. In order to render a reflective surface of the CGR object, one exemplary implementation involves synthesizing an environment map of a CGR environment representing a portion of a physical scene based on observed characteristics of the physical scene. In an implementation, generation of a complete environment map includes identifying pixels of the environment map with no corresponding texture and generating synthesized texture based on textural information associated with one or more camera images of the physical scene. In an implementation, a CGR object is rendered in the CGR environment, wherein an appearance of a reflective surface of the CGR object is determined based on the complete environment map of the CGR environment.

In various embodiments, a training application trains a machine learning model to modify portions of shapes when designing 3D objects. The training application converts first structural analysis data having a first resolution to first coarse structural analysis data having a second resolution that is lower than the first resolution. Subsequently, the training application generates one or more training sets based on a first shape, the first coarse structural analysis data, and a second shape that is derived from the first shape. Each training set is associated with a different portion of the first shape. The training application then performs one or more machine learning operations on the machine learning model using the training set(s) to generate a trained machine learning model. The trained machine learning model modifies at least a portion of a shape having the first resolution based on coarse structural analysis data having the second resolution.

The disclosed systems, components, methods, and processing steps are directed to determining user-item fit characteristics of an item for a user body part by accessing a three-dimensional (3D) reconstructed model of the user body part, accessing information about one or more 3D reference models of the item, the information for each 3D reference model including respective dimensional measurement, spatial, and geometrical attributes, performing a 3D matching process based on the 3D reconstructed model and the accessed information of the one or more 3D reference models to determine a best-fitting 3D reference model from the one or more 3D reference models, integrating the best-fitting 3D reference model with the 3D reconstructed model to provide a 3D best fit representation and displaying the 3D best fit representation along with visual indications of user-item fit characteristics.

Systems and methods for calculating external bone loss for alignment of pre-diseased joints comprising: generating a three-dimensional (“3D”) computer model of an operative area from at least two two-dimensional (“2D”) radiographic images, wherein at least a first radiographic image is captured at a first position, and wherein at least a second radiographic image is captured at a second position, and wherein the first position is different than the second position; identifying an area of bone loss on the 3D computer model; and applying a surface adjustment algorithm to calculate an external missing bone surface fitting the area of bone loss.

A computer system obtains at least one 3D scan of a body surface; automatically identifies, based on the at least one 3D scan, one or more features (e.g., nose, lips, eyes, eyebrows, cheekbones, or specific portions thereof, or other features) of the body surface; and generates a digital 3D model of the body surface. The digital 3D model includes the identified features of the human body surface. In an embodiment, the step of generating of the digital 3D model is based on the at least one 3D scan and the identified features of the body surface. In an embodiment, the digital 3D model comprises a 3D mesh file. The digital 3D model can be used in various ways. For example, output of a manufacturing process (e.g., a 3D printed item, a cosmetics product, a personal care product) can be based on the digital 3D model.

The Invention presents a system and a method for digitizing a human body shape from anthropometrical measurements. The proposed system and method allow reconstructing the 3D human body quickly and accurately, improving disadvantages of costly and timely traditional methods, which not only requires digitized persons to be naked or wear tight clothes but also could use hazardous lights to their health. The system in the invention includes two main modules and two supplementary blocks to reconstruct the 3D human body from anthropometric measurements, which are: (1) Input Block, (2) Pre-Processing Module, (3) Optimization Module, (4) Output Block. The method in the invention includes four steps: (1) Step 1a: collecting human body measurements, (2) Steps 1b: Initial Population; (3) Step 2: Optimizing; (4) Step 3: Displaying digitized human body shape.

The present technology generates a simplified version of a complex avatar by capturing images and 3-D volume information of segments of the complex avatar while the complex avatar is rendered. When the complex avatar is requested in an environment in which it is not desirable to display the complex avatar, the captured images and 3-D volume information can be used to provide a simplified version of the avatar. The simplified version of the avatar can have a similar visual appearance but can be easier to render. However, the present technology permits the user with the complex avatar to continue to have approximately the same visual appearance while avoiding the degraded performance on systems not capable of rendering the complex avatar quickly enough.

There is provided a method of representing a three dimensional (3D) object using univariate curves, comprising: receiving an initial definition of a 3D object representation, calculate a covering set of univariate curves, the covering set comprising at least one non-planar univariate curve, wherein the covering set of univariate curves represent the volume of the 3D object within a tolerance requirement, and generating a representation of the 3D object based on the set of univariate curves, wherein the set of univariate curves represent the volume of the 3D object.

A system is provided for generating a custom article to fit a target surface. During operation, the system compares an input dataset with a number of cut template cut meshes. A respective cut template cut mesh includes one or more cutting paths that correspond to a boundary of the mesh. Next, the system identifies a template cut mesh that produces a closest match with the input dataset, and applies global geometric transformations to the identified template cut mesh to warp the template cut mesh to conform to the input dataset. The system further refines and projects a set of boundary and landmark points from the template cut mesh to the input dataset to define cutting paths for the input dataset. Next, the system applies cutting paths to the input dataset to produce a cut-and-trimmed mesh.