Automatic detection of panoramic gestures

    公开(公告)号:US10397472B2

    公开(公告)日:2019-08-27

    申请号:US15901450

    申请日:2018-02-21

    Applicant: Google LLC

    Abstract: Aspects of the disclosure relate to capturing panoramic images using a computing device. For example, the computing device may record a set of video frames and tracking features each including one or more features that appear in two or more video frames of the set of video frames within the set of video frames may be determined. A set of frame-based features based on the displacement of the tracking features between two or more video frames of the set of video frames may be determined by the computing device. A set of historical feature values based on the set of frame-based features may also be determined by the computing device. The computing device may determine then whether a user is attempting to capture a panoramic image based on the set of historical feature values. In response, the computing device may capture a panoramic image.

    Depth map generation
    2.
    发明授权

    公开(公告)号:US10681336B2

    公开(公告)日:2020-06-09

    申请号:US14278471

    申请日:2014-05-15

    Applicant: Google LLC

    Abstract: Aspects of the disclosure relate generally to generating depth data from a video. As an example, one or more computing devices may receive an initialization request for a still image capture mode. After receiving the request to initialize the still image capture mode, the one or more computing devices may automatically begin to capture a video including a plurality of image frames. The one or more computing devices track features between a first image frame of the video and each of the other image frames of the video. Points corresponding to the tracked features may be generated by the one or more computing devices using a set of assumptions. The assumptions may include a first assumption that there is no rotation and a second assumption that there is no translation. The one or more computing devices then generate a depth map based at least in part on the points.

    Omnistereo capture for mobile devices

    公开(公告)号:US10334165B2

    公开(公告)日:2019-06-25

    申请号:US15723670

    申请日:2017-10-03

    Applicant: Google LLC

    Abstract: Systems and methods for capturing omnistereo content for a mobile device may include receiving an indication to capture a plurality of images of a scene, capturing the plurality of images using a camera associated with a mobile device and displaying on a screen of the mobile device and during capture, a representation of the plurality of images and presenting a composite image that includes a target capture path and an indicator that provides alignment information corresponding to a source capture path associated with the mobile device during capture of the plurality of images. The system may detect that a portion of the source capture path does not match a target capture path. The system can provide an updated indicator in the screen that may include a prompt to a user of the mobile device to adjust the mobile device to align the source capture path with the target capture path.

    DEFORMABLE NEURAL RADIANCE FIELDS
    4.
    发明公开

    公开(公告)号:US20240005590A1

    公开(公告)日:2024-01-04

    申请号:US18251995

    申请日:2021-01-14

    Applicant: GOOGLE LLC

    CPC classification number: G06T15/20 G06T15/55 G06T15/04

    Abstract: Techniques of image synthesis using a neural radiance field (NeRF) includes generating a deformation model of movement experienced by a subject in a non-rigidly deforming scene. For example, when an image synthesis system uses NeRFs, the system takes as input multiple poses of subjects for training data. In contrast to conventional NeRFs, the technical solution first expresses the positions of the subjects from various perspectives in an observation frame. The technical solution then involves deriving a deformation model, i.e., a mapping between the observation frame and a canonical frame in which the subject's movements are taken into account. This mapping is accomplished using latent deformation codes for each pose that are determined using a multilayer perceptron (MLP). A NeRF is then derived from positions and casted ray directions in the canonical frame using another MLP. New poses for the subject may then be derived using the NeRF.

    AUTOMATIC DETECTION OF PANORAMIC GESTURES
    6.
    发明申请

    公开(公告)号:US20180183997A1

    公开(公告)日:2018-06-28

    申请号:US15901450

    申请日:2018-02-21

    Applicant: Google LLC

    Abstract: Aspects of the disclosure relate to capturing panoramic images using a computing device. For example, the computing device may record a set of video frames and tracking features each including one or more features that appear in two or more video frames of the set of video frames within the set of video frames may be determined. A set of frame-based features based on the displacement of the tracking features between two or more video frames of the set of video frames may be determined by the computing device. A set of historical feature values based on the set of frame-based features may also be determined by the computing device. The computing device may determine then whether a user is attempting to capture a panoramic image based on the set of historical feature values. In response, the computing device may capture a panoramic image.

    Automatic detection of panoramic gestures

    公开(公告)号:US09936128B2

    公开(公告)日:2018-04-03

    申请号:US14717492

    申请日:2015-05-20

    Applicant: Google LLC

    Abstract: Aspects of the disclosure relate to capturing panoramic images using a computing device. For example, the computing device may record a set of video frames and tracking features each including one or more features that appear in two or more video frames of the set of video frames within the set of video frames may be determined. A set of frame-based features based on the displacement of the tracking features between two or more video frames of the set of video frames may be determined by the computing device. A set of historical feature values based on the set of frame-based features may also be determined by the computing device. The computing device may determine then whether a user is attempting to capture a panoramic image based on the set of historical feature values. In response, the computing device may capture a panoramic image.

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