Microsoft Technology Licensing, LLC

Erik Alexander Hill

Kathleen Carol Heasley

Jake Thomas Shields

Jonathan Gustav Paulovich

Constantin Dulu

Julien Pascal Christophe Valentin

Dylan Edmund Pierpont

Garret Paul Jacobson

Kevin James-Peddicord Luecke

Robert Neil Drury

Andrew Jackson Klein

Todd Omotani

Benjamin James Andrews

Travis Joseph Fodor

Xiao Bai Lu

Michael William Schultz

Brandon Kasey Harper

Gabriel Robert Maricich

Charles L Harrison

Techniques for intelligently repositioning a hologram for an object in a scene based on a past condition of the object and/or a planned future condition of the object are disclosed. A hologram is identified for an object in a scene. Identifying the hologram includes identifying a current location of the hologram within the scene. Time-based data associated with the object is accessed. The time-based data includes at least one of a past condition of the object or a planned future condition of the object. A new location for the hologram is selected within the scene. This selection is based on the time-based data. The hologram is then repositioned to the new location.

Smart placement of information based on dynamic environments

Generally discussed herein are examples of gesture-based extended reality (XR) with object recognition and tracking. A method, implemented by an extended reality (XR) device can include recognizing and tracking one or more objects in the image data, recognizing a gesture in the image data, analyzing the image data to determine whether a condition is satisfied, the condition indicating a recognized and tracked object of the one or more objects proximate which the recognized gesture is to be made, and in response to determining that the condition is satisfied, performing an augmentation of the image data based on satisfaction of the condition.

Extended reality gesture recognition proximate tracked object

Techniques and systems are provided for positioning mixed-reality devices within mixed-reality environments. The devices, which are configured to perform inside out tracking, transition between position tracking states in mixed-reality environments and utilize positional information from other inside out tracking devices that share the mixed-reality environments to identify/update positioning of the devices when they become disoriented within the environments and without requiring an extensive or full scan and comparison/matching of feature points that are detectable by the devices with mapped feature points of the maps associated with the mixed-reality environments. Such techniques can conserve processing and power consumption that would be required when performing a full or extensive scan and comparison of matching feature points. Such techniques can also enhance the accuracy and speed of positioning mixed-reality devices.

Mixed-reality device positioning based on shared location

A system receives input from a user to initiate a process of generating a holodouble of the user. The system obtains image data of the user and deconstructs the image data to obtain a set of sparse data that identifies one or more attributes associated with the image data the user. The system uses a holodouble training model to generate and train the holodouble of the user based on the set of sparse data and obtained image data. The system renders a representation of the holodouble to the user concurrently while capturing new image data of the user, receives input from the user comprising approval of the holodouble, and completes training of the holodouble by saving the holodouble for subsequent use. The subsequent use includes one or more remote visual communication sessions.

Holodouble: systems and methods for low-bandwidth and high-quality remote visual communication

Systems and methods are provided for generating, selecting, modifying and/or otherwise configuring occluder(s) used in mixed-reality environments. Pose information of a trackable device worn or carried by a user is determined. Based on that pose information, an assumption regarding the user's own pose is determined. An occluder is then configured in a manner to correspond to the assumed pose of the user for use in the mixed-reality environment. By generating the occluder in this manner, improved battery life by the trackable device can be achieved relative to conventional systems that rely entirely on iterative scanning of the user's body to determine body position.

Dynamic adjustments in mixed-reality environment based on positional assumptions and configurations

A computer implemented method includes recording data representative of a user experience sensed by a mixed reality device during a mixed reality experience of a user in a space, processing the recorded data to infer one or more actions performed by the user in the space during the mixed reality experience, and creating an augmented replay of the mixed reality experience based on the recorded data and inferred actions performed by the user during the mixed reality experience.

Reconstructing mixed reality contextually derived actions

Holodouble: systems and methods for low-bandwidth and high quality remote visual communication

Multiple sound systems are used to provide a realistic audio MR audio experience for one or more users. In one example, an MR space sound system has one or more speakers distributed within an MR space. MR device sound systems for users provides sound directly to the users wearing the MR devices. Audio signals representative of sound in the MR experience are mixed by each sound system to provide sounds that complement each other. Both sound systems provide sound to the users based on events occurring in the MR experience.

Mixed reality complementary systems

Improved techniques for mapping an environment are disclosed herein. These improvements are achieved by distinguishing between different environmental regions and by selectively using scanning data of the environment to generate a 3D representation of at least one, but not all, of the environment's regions. Initially, 3D depth scanning data is accessed. A boundary associated with the environment is identified. This boundary divides the environment into at least two regions, including a first and second region. Based on the boundary, a first portion of the scanning data is classified as corresponding to the first region and a second portion of the scanning data is classified as corresponding to the second region. After filtering the second portion from the scanning data, the filtered scanning data is used to generate the 3D representation. Consequently, the 3D representation is limited by the boundary and visually represents the first region but not the second.

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Redmond, WA, United States of America

Erik Alexander Hill