Provided is method and system for organizing a virtual showroom with one or more 3d images. Scripts are generated from the input images provided by the user, for generating 3D images of the products in the showroom. The generated 3D images can be in folded form, hanger display or mannequin.

A method for displaying virtual content to a user, the method includes determining an accommodation of the user's eyes. The method also includes delivering, through a first waveguide of a stack of waveguides, light rays having a first wavefront curvature based at least in part on the determined accommodation, wherein the first wavefront curvature corresponds to a focal distance of the determined accommodation. The method further includes delivering, through a second waveguide of the stack of waveguides, light rays having a second wavefront curvature, the second wavefront curvature associated with a predetermined margin of the focal distance of the determined accommodation.

Embodiments of the invention are directed to systems, methods, and computer program products for adaptive augmented reality for dynamic processing of spatial component parameters based on detecting accommodation factors in real time. The system is further configured for dynamic capture, analysis and modification of spatial component parameters in a virtual reality (VR) space and real-time transformation to composite plan files. Moreover, the system comprises one or more composite credential sensor devices, comprising one or more VR spatial sensor devices configured for capture and imaging of VR spatial movement and position credentials. The system is also configured to dynamically transform and adapt a first immersive virtual simulation structure associated with the first physical location sector, in real-time, based on detecting and analyzing mobility assist devices associated with users.

A system for determining volume of a selectable region is configurable to (i) obtain user input directed to a 3D representation of a set of 2D images and (ii) based on the user input, selectively modify one or more mask pixels of one or more respective selection masks. Each 2D image of the set of 2D images is associated with a respective selection mask. The 3D representation represents pixels of the set of 2D images with corresponding voxels. The user input selects one or more voxels of the 3D representation. The one or more mask pixels is associated with one or more pixels of the set of 2D images that correspond to the one or more voxels of the 3D representation selected via the user input.

One or more custom actions are stored in memory. Each of the custom actions is associated with a pattern of physical movement and a threshold. Physical movement data captured by a user device of the user is received and mapped to an identified one of the custom actions. When the physical movement data matches the associated pattern of physical movement within the associated threshold, it is determined that the user is authorized to access the identified custom action.

Methods, systems, and storage media for recording moments as they are occurring and utilizing a virtual assistant to re-play those moments as a fully or partially immersive experience are disclosed. Exemplary implementations may: record data for a particular moment as the moment is occurring and utilize a virtual assistant to replay the moment as a fully or partially immersive experience. The recorded data may include indicators of a plurality of sensory perceptions for the recorded moment.

A map database creation method is provided. The method includes: obtaining a factor set including factors; dividing a map database into levels based on the factors, and taking each interval of the last level as one sub-database; creating an initial map based on a factor value of each factor corresponding to each sub-database, and creating the sub-database as an initial map database by storing the corresponding initial map in the sub-database; finding the initial map matching a current lighting condition from the initial map database based on the current lighting condition, and taking the found initial map as a positioning map; and performing a visual positioning based on the positioning map, creating an expanded map corresponding to the current lighting condition based on the visual positioning, and creating the sub-database corresponding to the current lighting condition as an expanded map database by storing the corresponding expanded map in the sub-database.

Methods and systems for a virtual experience where a user moves physically to move his or her ‘agent’, a position in the virtual space that determines which virtual content the user may interact with. If the virtual space contains obstacles, and the user moves such that the agent would intersect with one, either (a) move the correlation vector between the virtual space and real space to counteract the user's physical movement, preventing the user from penetrating the obstacle, or (b) allow the user to proceed, but become separated from his or her agent. Also described are applying these methods if the real space is too small to fit the virtual space, if the agent has a speed limitation that the user violates, how to direct the agent when it is separated from the user, and how to handle three-dimensional obstacles, real-world obstacles, and multiple users.

A method is shown for providing a user interface for a 3D environment of 360° images. The method includes displaying a first 360 degree image in a sequence of 360 degree images; receiving user input to interact with one of a plurality of points of interest detected within the first 360 degree image; and processing the interaction. Each point of interest is associated with a 3D coordinate. A system and software are also disclosed.

The disclosure notably relates to a computer-implemented method of machine-learning. The method includes obtaining a dataset including 3D modeled objects which each represent a respective mechanical part and further includes providing a set of neural networks. Each neural network has respective weights. Each neural network is configured for inference of 3D modeled objects. The method further includes modifying respective weights of the neural networks by minimizing a loss. For each 3D modeled object, the loss selects a term among a plurality of terms. Each term penalizes a disparity between the 3D modeled object and a respective 3D modeled object inferred by a respective neural network of the set. The selected term is a term among the plurality of terms for which the disparity is the least penalized. This constitutes an improved method of machine-learning with a dataset including 3D modeled objects which each represent a respective mechanical part.