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公开(公告)号：US10902551B1
公开(公告)日：2021-01-26
申请号：US16717013
申请日：2019-12-17
Applicant: X Development LLC
IPC: G06T3/00 , G06T7/194 , G06T7/70 , G06K9/62 , G06F3/0484
Abstract: Systems and methods for augmenting a data set are provided. An example method may include locating a foreground object disposed within a seed image, identifying an object class corresponding to the foreground object, and, based on the identified object class, determining a target value for an object property of the foreground object. The example method may also include applying a transformation function to transform the foreground object into a transformed object, where the transformation function modifies the object property of the foreground object from having an initial value to having the target value. The example method may further include transplanting the transformed object into a background image so as to produce an augmented image and augmenting an initial set of images with the augmented image so as to produce an augmented set of images for training a predictive model.
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公开(公告)号：US20220222772A1
公开(公告)日：2022-07-14
申请号：US17657464
申请日：2022-03-31
Applicant: X Development LLC
IPC: G06T3/00 , G06T7/194 , G06T7/70 , G06K9/62 , G06F3/0484
Abstract: Systems and methods for augmenting a data set are provided. An example method may include locating a foreground object disposed within a seed image, identifying an object class corresponding to the foreground object, and, based on the identified object class, determining a target value for an object property of the foreground object. The example method may also include applying a transformation function to transform the foreground object into a transformed object, where the transformation function modifies the object property of the foreground object from having an initial value to having the target value. The example method may further include transplanting the transformed object into a background image so as to produce an augmented image and augmenting an initial set of images with the augmented image so as to produce an augmented set of images for training a predictive model.
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Patent Agency Ranking
公开(公告)号：US11042783B2
公开(公告)日：2021-06-22
申请号：US16734285
申请日：2020-01-03
Applicant: X Development LLC
Inventor： Alexa Greenberg
Abstract: Techniques described herein relate to generating a posteriori knowledge about where objects are typically located within environments to improve object location. In various implementations, output from vision sensor(s) of a robot may include visual frame(s) that capture at least a portion of an environment in which a robot operates/will operate. The visual frame(s) may be applied as input across a machine learning model to generate output that identifies potential location(s) of an object of interest. The robot's position/pose may be altered based on the output to relocate one or more of the vision sensors. One or more subsequent visual frames that capture at least a not-previously-captured portion of the environment may be applied as input across the machine learning model to generate subsequent output identifying the object of interest. The robot may perform task(s) that relate to the object of interest.
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公开(公告)号：US10572775B2
公开(公告)日：2020-02-25
申请号：US15832705
申请日：2017-12-05
Applicant: X Development LLC
Inventor： Alexa Greenberg
Abstract: Techniques described herein relate to generating a posteriori knowledge about where objects are typically located within environments to improve object location. In various implementations, output from vision sensor(s) of a robot may include visual frame(s) that capture at least a portion of an environment in which a robot operates/will operate. The visual frame(s) may be applied as input across a machine learning model to generate output that identifies potential location(s) of an object of interest. The robot's position/pose may be altered based on the output to relocate one or more of the vision sensors. One or more subsequent visual frames that capture at least a not-previously-captured portion of the environment may be applied as input across the machine learning model to generate subsequent output identifying the object of interest. The robot may perform task(s) that relate to the object of interest.
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公开(公告)号：US11321809B2
公开(公告)日：2022-05-03
申请号：US17124103
申请日：2020-12-16
Applicant: X Development LLC
IPC: G06T3/00 , G06T7/194 , G06T7/70 , G06K9/62 , G06F3/0484
Abstract: Systems and methods for augmenting a data set are provided. An example method may include locating a foreground object disposed within a seed image, identifying an object class corresponding to the foreground object, and, based on the identified object class, determining a target value for an object property of the foreground object. The example method may also include applying a transformation function to transform the foreground object into a transformed object, where the transformation function modifies the object property of the foreground object from having an initial value to having the target value. The example method may further include transplanting the transformed object into a background image so as to produce an augmented image and augmenting an initial set of images with the augmented image so as to produce an augmented set of images for training a predictive model.
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公开(公告)号：US20210183008A1
公开(公告)日：2021-06-17
申请号：US17124103
申请日：2020-12-16
Applicant: X Development LLC
IPC: G06T3/00 , G06K9/62 , G06T7/70 , G06T7/194 , G06F3/0484
Abstract: Systems and methods for augmenting a data set are provided. An example method may include locating a foreground object disposed within a seed image, identifying an object class corresponding to the foreground object, and, based on the identified object class, determining a target value for an object property of the foreground object. The example method may also include applying a transformation function to transform the foreground object into a transformed object, where the transformation function modifies the object property of the foreground object from having an initial value to having the target value. The example method may further include transplanting the transformed object into a background image so as to produce an augmented image and augmenting an initial set of images with the augmented image so as to produce an augmented set of images for training a predictive model.
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公开(公告)号：US20190171911A1
公开(公告)日：2019-06-06
申请号：US15832705
申请日：2017-12-05
Applicant: X Development LLC
Inventor： Alexa Greenberg
CPC classification number: G06K9/6262 , B25J9/163 , B25J9/1697 , G05B13/027 , G05B2219/33038 , G05B2219/39046 , G05B2219/39543 , G06K9/00664 , G06K9/32 , G06N3/04 , G06N3/0454 , G06N3/08 , G06N3/084 , G06T7/97 , G06T2207/20081
Abstract: Techniques described herein relate to generating a posteriori knowledge about where objects are typically located within environments to improve object location. In various implementations, output from vision sensor(s) of a robot may include visual frame(s) that capture at least a portion of an environment in which a robot operates/will operate. The visual frame(s) may be applied as input across a machine learning model to generate output that identifies potential location(s) of an object of interest. The robot's position/pose may be altered based on the output to relocate one or more of the vision sensors. One or more subsequent visual frames that capture at least a not-previously-captured portion of the environment may be applied as input across the machine learning model to generate subsequent output identifying the object of interest. The robot may perform task(s) that relate to the object of interest.
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