The present technology is directed to visualizing a Wi-Fi signal propagation in 3-D based on a building plan defined with implicit geometry. The present technology can extract data from a building plan file where a 3-D space and objects in a building plan are defined with implicit geometry, transform the implicit geometry to explicit geometry for the 3-D space and the objects to translate a positioning of the 3-D space and objects from a local coordinate system to a global coordinate system, calculate a RF propagation pattern in the 3-D space based on a RF propagation model for a plurality of Wi-Fi access points located in the 3-D space, and present a 3-D visualization of the RF propagation pattern in the 3-D space.

A method of detecting a protrusion in an intestinal tract in a computer according to an embodiment of the present disclosure includes acquiring a three-dimensional model of the intestinal tract scanned by a scanning device, the three-dimensional model comprising three-dimensional data of the intestinal tract; mapping, in the computer, the three-dimensional model to a two-dimensional plane in an area-preserving manner; and detecting an area of the protrusion in the two-dimensional plane. The method can replace traditional modes such as enteroscopy, and the protrusion in the intestinal tract is detected in a painless and low-cost mode.

In an example a method includes receiving, at processing circuitry, beam lattice data modelling at least part of a three-dimensional object to be generated using additive manufacturing as a beam lattice. A volumetric data model may be determined from the beam lattice data. Determining the volumetric data model may comprise dividing a volume containing the beam lattice data into sub-volumes and categorising the sub-volumes into (I) interior sub-volumes, which are wholly within a beam of the beam lattice; (ii) exterior sub-volumes which are wholly outside the beams of the beam lattice; and (ii) boundary sub-volumes which partially coincide with a beam of the beam lattice. The method may further comprise subdividing boundary sub-volumes and categorising the subdivided sub-volumes until a threshold volume size of boundary sub-volume is reached.

In one embodiment, a method includes generating a front panel of a garment based on one or more images including the garment, generating a back panel of the garment, aligning the front panel and the back panel in a three-dimensional space so that the front panel is in front of a three-dimensional body and the back panel is behind the three-dimensional body, identifying one or more pairs of boundary segments of the front panel and the back panel, wherein each pair of boundary segments of the front panel and the back panel are to be attached together, and generating a digital garment by attaching each of the identified one or more pairs of boundary segments of the front panel and the back panel through a plurality of iterative simulations using a physics simulation model.

Embodiments are generally directed to generating and providing normalized representation in a three-dimensional (3D) model.

According to an aspect, a method includes receiving a first three-dimensional model (3D) model of at least a body part of a person, receiving a second 3D model of a wearable device, and predicting, by at least one machine-learning (ML) model, a plurality of contact points between the first 3D model and the second 3D model.

A method of reconstructing a gingival profile comprising generating, by a processor, a defined cross section of an arch form model extending through a tooth axis of a given tooth and a defined gingiva region; identifying within a tooth cross section profile of the defined cross section a set of reference points for generating a parametric curve defining at least a portion of the tooth cross section profile; generating the parametric curve based on the set of reference points; generating a first undefined cross section of the arch form model extending through the tooth axis of the given tooth and an defined gingiva region; constructing in the first undefined cross section, at least a portion of the parametric curve, thereby generating a first reconstructed gingival profile, and updating the arch form model with the first reconstructed gingival profile; and storing the arch form model including the reconstructed gingival profile.

A user’s environment is scanned and an augmented reality game such as a treasure is set up based on the scan. The user needs to use a phone to uncover clues in a game environment that is customized to user’s own personal real-world environment, which is discovered using SLAM or GPS so that a map of furniture can be built. The game hides a virtual object behind a virtualized image of the real-world furniture. Machine learning may be used to train a model with common objects and where interesting hidden spaces could exist. Given the user’s inputted data, real world physical room data and objects are used to determine a likely location to hide a virtual object.

An object management system according to one embodiment receives, from a user terminal, inquiry data indicating a combination of a target virtual object and a target parent object, refers to a database storing object relationship data indicating a hierarchical relationship between a plurality of objects, and allows the user terminal arrangement of the target virtual object in the virtual space when the combination indicated by the inquiry data is registered in the object relationship data, and disallows the arrangement of the user terminal when the combination is not registered in the object relationship data.

A computer-implemented method and system of automatically detecting and removing extraneous material from a digital dental impression includes detecting one or more dental features in a digital dental impression, filtering the one or more dental features, digitally joining the one or more dental features, and determining one or more regions of interest from the joined one or more digital dental features.