Anchor Objects for Artificial Reality Environments

    公开(公告)号:US20240362879A1

    公开(公告)日:2024-10-31

    申请号:US18645825

    申请日:2024-04-25

    IPC分类号: G06T19/20 G06F3/01 G06T19/00

    摘要: Aspects of the present disclosure relate to an anchor object to which virtual objects can be consistently mapped in an artificial reality (XR) environment. In some implementations, the virtual objects can include avatars of users accessing the XR environment on respective XR systems. The anchor object can be a virtual object, such as a menu or shape, or a physical object, such as a stage computing device positioned in the users' surrounding real-world environments. The users can move the anchor object as rendered on their respective XR systems, which causes reciprocal movement of their corresponding avatars on other users' XR systems. Thus, virtual objects can be consistently referenced across all of the XR systems accessing the XR environment.

    SYSTEM AND METHOD FOR AUGMENTED INTELLIGENCE IN DENTAL FILE SEGMENTATION

    公开(公告)号:US20240355080A1

    公开(公告)日:2024-10-24

    申请号:US18687440

    申请日:2022-05-20

    申请人: AiCAD Dental Inc.

    摘要: A computer-implemented system and method of generating two-dimensional (2D) descriptors for three-dimensional (3D) dental objects. The system comprises an indexed slicer to receive a mesh file of a dental object and slice the mesh into a plurality of slices, each slice comprising a cross-sectional boundary of the dental object and a radial encoder assigning an indexing centroid and measuring a plurality of rays from the indexing centroid to the cross-sectional boundary. The 3D mesh file can then be stored as a 2D descriptor matrix in a dental descriptor database. Dental objects can be searched in the descriptor database based on their 2D descriptor matrixes and matched to other similar dental objects, preferably in a graphical processing unit, for use in anomaly detection, diagnostics, and prosthetic design.

    PRODUCT PLACEMENT SYSTEMS AND METHODS FOR 3D PRODUCTIONS

    公开(公告)号:US20240355050A1

    公开(公告)日:2024-10-24

    申请号:US18137290

    申请日:2023-04-20

    申请人: Adeia Guides Inc.

    IPC分类号: G06T17/10 G06T19/20

    摘要: Systems and methods for replacing a 3D container in a 3D scene with a replacement 3D object are described. A 3D scene is rendered, and a determination is made as to whether the 3D scene includes a 3D container. If it does, attributes and rules associated with the 3D container are obtained. A replacement 3D object that adheres to the obtained attributes and rules is selected. The selection may be based on replacement 3D objects from submission from object servers. The object servers may also bid to place the replacement 3D object. Once a replacement 3D object is selected, it is used to replace the 3D container at the time of rendering the 3D scene.

    USER CONTROLLED THREE-DIMENSIONAL SCENE
    9.
    发明公开

    公开(公告)号:US20240346792A1

    公开(公告)日:2024-10-17

    申请号:US18637415

    申请日:2024-04-16

    申请人: Malay Kundu

    发明人: Malay Kundu

    摘要: The present disclosure relates generally to a system and method for a user to control a virtual representation of themselves within a three-dimensional virtual world. The system and method enable utilizing a two-dimensional image or video data of user with extracted depth information to position themselves in a three-dimensional scene. It also provides a control system and method for a user to control the virtual representation of themselves using the output video as a visual feedback mechanism in a three-dimensional space including the virtual representation of themselves. A user interacts with other virtual objects or items in a scene or even with other users visualized in the scene.

    MACHINE LEARNING DEVICE AND VEHICLE
    10.
    发明公开

    公开(公告)号:US20240346752A1

    公开(公告)日:2024-10-17

    申请号:US18624468

    申请日:2024-04-02

    发明人: Toshimi OKUBO

    IPC分类号: G06T17/00 G06T5/60 G06T19/20

    摘要: A machine learning device includes one or more processors, and one or more memories coupled to the one or more processors. The one or more processors are configured to cooperate with a program in the one or more memories to execute a process including acquiring image combinations multiple times, each of the image combinations including brightness images captured at different imaging positions and a training image associated with one of the brightness images, performing a manipulation process that includes manipulating the brightness images, and generating a machine learning model configured to receive the manipulated brightness images and the training image as input. The manipulation process includes a noise addition process that includes adding partial noise to different positions in the brightness images in an image combination of the image combinations.