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公开(公告)号：US20210104096A1
公开(公告)日：2021-04-08
申请号：US16591359
申请日：2019-10-02
Applicant: Google LLC
Inventor： Artsiom Ablavatski , Yury Kartynnik , Ivan Grishchenko , Matthias Grundmann
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a neural network model to predict mesh vertices corresponding to a three-dimensional surface geometry of an object depicted in an image.
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公开(公告)号：US20190205654A1
公开(公告)日：2019-07-04
申请号：US16298327
申请日：2019-03-11
Applicant: Google LLC
Inventor： Matthias Grundmann , Alexandra Ivanna Hawkins , Sergey Ioffe
CPC classification number: G06K9/00765 , G06K9/00751 , G06K9/623
Abstract: Methods, systems, and media for summarizing a video with video thumbnails are provided. In some embodiments, the method comprises: receiving a plurality of video frames corresponding to the video and associated information associated with each of the plurality of video frames; extracting, for each of the plurality of video frames, a plurality of features; generating candidate clips that each includes at least a portion of the received video frames based on the extracted plurality of features and the associated information; calculating, for each candidate clip, a clip score based on the extracted plurality of features from the video frames associated with the candidate clip; calculating, between adjacent candidate clips, a transition score based at least in part on a comparison of video frame features between frames from the adjacent candidate clips; selecting a subset of the candidate clips based at least in part on the clip score and the transition score associated with each of the candidate clips; and automatically generating an animated video thumbnail corresponding to the video that includes a plurality of video frames selected from each of the subset of candidate clips.
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公开(公告)号：US10191920B1
公开(公告)日：2019-01-29
申请号：US14833887
申请日：2015-08-24
Applicant: Google LLC
Inventor： Matthias Grundmann , Karthik Raveendran , Daniel Castro Chin
IPC: G06F17/30 , G06F3/0484 , G06F3/0482 , G06K9/00 , G06T11/60
Abstract: A computing device is described that includes a camera configured to capture an image of a user of the computing device, a memory configured to store the image of the user, at least one processor, and at least one module. The at least one module is operable by the at least one processor to obtain, from the memory, an indication of the image of the user of the computing device, determine, based on the image, a first emotion classification tag, and identify, based on the first emotion classification tag, at least one graphical image from a database of pre-classified images that has an emotional classification that is associated with the first emotion classification tag. The at least one module is further operable by the at least one processor to output, for display, the at least one graphical image.
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公开(公告)号：US20230410329A1
公开(公告)日：2023-12-21
申请号：US18460338
申请日：2023-09-01
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Tkachenka , Andrei Vakunov , Matthias Grundmann
CPC classification number: G06T7/251 , G06T7/75 , G06V40/28 , G06T2207/30196 , G06T2207/20081
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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公开(公告)号：US20230326073A1
公开(公告)日：2023-10-12
申请号：US18335614
申请日：2023-06-15
Applicant: Google LLC
Inventor： Jianing Wei , Matthias Grundmann
CPC classification number: G06T7/74 , G06T19/006 , G06T19/20 , G01C19/00 , G02B27/017 , G06T2219/2004 , G06T2219/2016
Abstract: The present disclosure provides systems and methods for calibration-free instant motion tracking useful, for example, for rending virtual content in augmented reality settings. In particular, a computing system can iteratively augment image frames that depict a scene to insert virtual content at an anchor region within the scene, including situations in which the anchor region moves relative to the scene. To do so, the computing system can estimate, for each of a number of sequential image frames: a rotation of an image capture system that captures the image frames; and a translation of the anchor region relative to an image capture system, thereby providing sufficient information to determine where and at what orientation to render the virtual content within the image frame.
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Patent Agency Ranking
公开(公告)号：US11494990B2
公开(公告)日：2022-11-08
申请号：US16620264
申请日：2019-10-07
Applicant: Google LLC
Inventor： Bryan Woods , Jianing Wei , Sundeep Vaddadi , Cheng Yang , Konstantine Tsotsos , Keith Schaefer , Leon Wong , Keir Banks Mierle , Matthias Grundmann
IPC: G06T19/00 , G06F3/04815 , G06T19/20
Abstract: In a general aspect, a method can include receiving data defining an augmented reality (AR) environment including a representation of a physical environment, and changing tracking of an AR object within the AR environment between region-tracking mode and plane-tracking mode.
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公开(公告)号：US11436755B2
公开(公告)日：2022-09-06
申请号：US16988683
申请日：2020-08-09
Applicant: Google LLC
Inventor： Tingbo Hou , Matthias Grundmann , Liangkai Zhang , Jianing Wei , Adel Ahmadyan
Abstract: Example embodiments allow for fast, efficient determination of bounding box vertices or other pose information for objects based on images of a scene that may contain the objects. An artificial neural network or other machine learning algorithm is used to generate, from an input image, a heat map and a number of pairs of displacement maps. The location of a peak within the heat map is then used to extract, from the displacement maps, the two-dimensional displacement, from the location of the peak within the image, of vertices of a bounding box that contains the object. This bounding box can then be used to determine the pose of the object within the scene. The artificial neural network can be configured to generate intermediate segmentation maps, coordinate maps, or other information about the shape of the object so as to improve the estimated bounding box.
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公开(公告)号：US20220076433A1
公开(公告)日：2022-03-10
申请号：US17527463
申请日：2021-11-16
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Vakunov , Andrei Tkachenka , Matthias Grundmann
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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公开(公告)号：US10956749B2
公开(公告)日：2021-03-23
申请号：US16298327
申请日：2019-03-11
Applicant: Google LLC
Inventor： Matthias Grundmann , Alexandra Ivanna Hawkins , Sergey Ioffe
Abstract: Methods, systems, and media for summarizing a video with video thumbnails are provided. In some embodiments, the method comprises: receiving a plurality of video frames corresponding to the video and associated information associated with each of the plurality of video frames; extracting, for each of the plurality of video frames, a plurality of features; generating candidate clips that each includes at least a portion of the received video frames based on the extracted plurality of features and the associated information; calculating, for each candidate clip, a clip score based on the extracted plurality of features from the video frames associated with the candidate clip; calculating, between adjacent candidate clips, a transition score based at least in part on a comparison of video frame features between frames from the adjacent candidate clips; selecting a subset of the candidate clips based at least in part on the clip score and the transition score associated with each of the candidate clips; and automatically generating an animated video thumbnail corresponding to the video that includes a plurality of video frames selected from each of the subset of candidate clips.
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公开(公告)号：US10514818B2
公开(公告)日：2019-12-24
申请号：US15092102
申请日：2016-04-06
Applicant: Google LLC
Inventor： Sergey Ioffe , Vivek Kwatra , Matthias Grundmann
IPC: G06F3/0481 , G06F16/58 , G06F16/438
Abstract: A computer-implemented method, computer program product, and computing system is provided for interacting with images having similar content. In an embodiment, a method may include identifying a plurality of photographs as including a common characteristic. The method may also include generating a flipbook media item including the plurality of photographs. The method may further include associating one or more interactive control features with the flipbook media item.
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