Natural language understanding for visual tagging

    公开(公告)号:US12204869B2

    公开(公告)日:2025-01-21

    申请号:US16861097

    申请日:2020-04-28

    Applicant: Fyusion, Inc.

    Abstract: A tag characterizing a portion of a multi-view interactive digital media representation (MVIDMR) may be determined by applying a grammar to natural language data. The MVIDMR may include images of an object and may be navigable in one or more dimensions. An object model location for the tag identifying a location within a three-dimensional object model may be determined by applying the grammar to the natural language data. The tag may then be applied to the MVIDMR by associating it with two or more of the images at positions determined based on the object model location.

    Method and apparatus for 3-D auto tagging

    公开(公告)号:US11488380B2

    公开(公告)日:2022-11-01

    申请号:US17338217

    申请日:2021-06-03

    Applicant: Fyusion, Inc.

    Abstract: A multi-view interactive digital media representation (MVIDMR) of an object can be generated from live images of an object captured from a camera. Selectable tags can be placed at locations on the object in the MVIDMR. When the selectable tags are selected, media content can be output which shows details of the object at location where the selectable tag is placed. A machine learning algorithm can be used to automatically recognize landmarks on the object in the frames of the MVIDMR and a structure from motion calculation can be used to determine 3-D positions associated with the landmarks. A 3-D skeleton associated with the object can be assembled from the 3-D positions and projected into the frames associated with the MVIDMR. The 3-D skeleton can be used to determine the selectable tag locations in the frames of the MVIDMR of the object.

    Method and apparatus for 3-D auto tagging

    公开(公告)号:US11055534B2

    公开(公告)日:2021-07-06

    申请号:US16778981

    申请日:2020-01-31

    Applicant: Fyusion, Inc.

    Abstract: A multi-view interactive digital media representation (MVIDMR) of an object can be generated from live images of an object captured from a camera. Selectable tags can be placed at locations on the object in the MVIDMR. When the selectable tags are selected, media content can be output which shows details of the object at location where the selectable tag is placed. A machine learning algorithm can be used to automatically recognize landmarks on the object in the frames of the MVIDMR and a structure from motion calculation can be used to determine 3-D positions associated with the landmarks. A 3-D skeleton associated with the object can be assembled from the 3-D positions and projected into the frames associated with the MVIDMR. The 3-D skeleton can be used to determine the selectable tag locations in the frames of the MVIDMR of the object.

    NATURAL LANGUAGE UNDERSTANDING FOR VISUAL TAGGING

    公开(公告)号:US20200257862A1

    公开(公告)日:2020-08-13

    申请号:US16861097

    申请日:2020-04-28

    Applicant: Fyusion, Inc.

    Abstract: A tag characterizing a portion of a multi-view interactive digital media representation (MVIDMR) may be determined by applying a grammar to natural language data. The MVIDMR may include images of an object and may be navigable in one or more dimensions. An object model location for the tag identifying a location within a three-dimensional object model may be determined by applying the grammar to the natural language data. The tag may then be applied to the MVIDMR by associating it with two or more of the images at positions determined based on the object model location.

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