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公开(公告)号：US20240256035A1
公开(公告)日：2024-08-01
申请号：US18588168
申请日：2024-02-27
Applicant: Microsoft Technology Licensing, LLC
CPC classification number: G06F3/013 , G06F21/32 , G06N3/04 , G06T7/73 , G06V40/16 , H04N23/00 , G06T2207/20084
Abstract: Aspects of the present disclosure relate to systems and methods for controlling a function of a computing system using gaze detection. In examples, one or more images of a user are received and gaze information may be determined from the received one or more images. Non-gaze information may be received when the gaze information is determined to satisfy a condition. Accordingly, a function may be enabled based on the received non-gaze information. In examples, the gaze information may be determined by extracting a plurality of features from the received one or more images, providing the plurality of features to a neural network, and determining, utilizing the neural network, a location at a display device at which a gaze of the user is directed.
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公开(公告)号：US20180232571A1
公开(公告)日：2018-08-16
申请号：US15936076
申请日：2018-03-26
Applicant: Microsoft Technology Licensing, LLC
Inventor： Steven Nabil BATHICHE , Vivek PRADEEP , Alexander Norman BENNETT , Daniel Gordon O'NEIL , Anthony Christian REED , Krzysztof Jan LUCHOWIEC , Tsitsi Isabel KOLAWOLE
CPC classification number: G06K9/00369 , G06F3/167 , G10L15/22 , G10L15/24 , G10L2015/227 , H05B37/0227 , Y02B20/48
Abstract: An intelligent assistant device is configured to communicate non-verbal cues. Image data indicating presence of a human is received from one or more cameras of the device. In response, one or more components of the device are actuated to non-verbally communicate the presence of the human. Data indicating context information of the human is received from one or more of the sensors. Using at least this data one or more contexts of the human are determined, and one or more components of the device are actuated to non-verbally communicate the one or more contexts of the human.
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公开(公告)号：US20240184852A1
公开(公告)日：2024-06-06
申请号：US18435405
申请日：2024-02-07
Applicant: Microsoft Technology Licensing, LLC
Inventor： Hamidreza Vaezi JOZE , Vivek PRADEEP , Karthik VIJAYAN
IPC: G06F18/214 , G06F18/21 , G06F18/211 , G06N3/04 , G06N3/08 , G06V40/10 , G06V40/16
CPC classification number: G06F18/2148 , G06F18/211 , G06F18/2155 , G06F18/2163 , G06N3/04 , G06N3/08 , G06V40/10 , G06V40/161 , G06V2201/07
Abstract: A method of training a neural network for detecting target features in images is described. The neural network is trained using a first data set that includes labeled images, where at least some of the labeled images having subjects with labeled features, including: dividing each of the labeled images of the first data set into a respective plurality of tiles, and generating, for each of the plurality of tiles, a plurality of feature anchors that indicate target features within the corresponding tile. Target features that correspond to the plurality of feature anchors are detected in a second data set of unlabeled images. Images of the second data set having target features that were not detected are labeled. A third data set that includes the first data set and the labeled images of the second data set is generated. The neural network is trained using the third data set.
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公开(公告)号：US20220358332A1
公开(公告)日：2022-11-10
申请号：US17314466
申请日：2021-05-07
Applicant: Microsoft Technology Licensing, LLC
Inventor： Hamidreza Vaezi JOZE , Vivek PRADEEP , Karthik VIJAYAN
Abstract: A method of training a neural network for detecting target features in images is described. The neural network is trained using a first data set that includes labeled images, where at least some of the labeled images having subjects with labeled features, including: dividing each of the labeled images of the first data set into a respective plurality of tiles, and generating, for each of the plurality of tiles, a plurality of feature anchors that indicate target features within the corresponding tile. Target features that correspond to the plurality of feature anchors are detected in a second data set of unlabeled images. Images of the second data set having target features that were not detected are labeled. A third data set that includes the first data set and the labeled images of the second data set is generated. The neural network is trained using the third data set.
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公开(公告)号：US20170285763A1
公开(公告)日：2017-10-05
申请号：US15623332
申请日：2017-06-14
Applicant: Microsoft Technology Licensing, LLC
Inventor： David KIM , Shahram IZADI , Vivek PRADEEP , Steven BATHICHE , Timothy Andrew LARGE , Karlton David POWELL
IPC: G06F3/01 , H04N5/33 , G06F3/03 , G06F3/042 , G06F3/041 , G06K9/20 , G06K9/52 , G06K9/00 , G01B11/24 , G06K9/46 , H04N13/02
CPC classification number: G06F3/017 , G01B11/24 , G06F3/0325 , G06F3/0416 , G06F3/0421 , G06F3/0425 , G06K9/00355 , G06K9/00362 , G06K9/2036 , G06K9/4604 , G06K9/52 , H04N5/33 , H04N13/204
Abstract: A 3D silhouette sensing system is described which comprises a stereo camera and a light source. In an embodiment, a 3D sensing module triggers the capture of pairs of images by the stereo camera at the same time that the light source illuminates the scene. A series of pairs of images may be captured at a predefined frame rate. Each pair of images is then analyzed to track both a retroreflector in the scene, which can be moved relative to the stereo camera, and an object which is between the retroreflector and the stereo camera and therefore partially occludes the retroreflector. In processing the image pairs, silhouettes are extracted for each of the retroreflector and the object and these are used to generate a 3D contour for each of the retroreflector and object.
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Patent Agency Ranking
公开(公告)号：US20240273104A1
公开(公告)日：2024-08-15
申请号：US18649458
申请日：2024-04-29
Applicant: Microsoft Technology Licensing, LLC
Inventor： Eric Chris Wolfgang SOMMERLADE , Vivek PRADEEP , Steven N. BATHICHE , Nathan LUQUETTA-FISH
IPC: G06F16/2457 , G06F16/22 , G06F40/30
CPC classification number: G06F16/24575 , G06F16/2228 , G06F40/30
Abstract: Methods and systems for generating and using a semantic index are provided. In some examples, content data is received. The content data includes a plurality of subsets of content data. Each of the plurality of subsets of content data are labelled, based on a semantic context corresponding to the content data. The plurality of subsets of content data and their corresponding labels are stored. The plurality of subsets of content data are grouped, based on their labels, thereby generating one or more groups of subsets of content data. Further, a computing device is adapted to perform an action, based on the one or more groups of subsets of content data.
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公开(公告)号：US20220221932A1
公开(公告)日：2022-07-14
申请号：US17146719
申请日：2021-01-12
Applicant: Microsoft Technology Licensing, LLC
Abstract: Aspects of the present disclosure relate to systems and methods for controlling a function of a computing system using gaze detection. In examples, one or more images of a user are received and gaze information may be determined from the received one or more images. Non-gaze information may be received when the gaze information is determined to satisfy a condition. Accordingly, a function may be enabled based on the received non-gaze information. In examples, the gaze information may be determined by extracting a plurality of features from the received one or more images, providing the plurality of features to a neural network, and determining, utilizing the neural network, a location at a display device at which a gaze of the user is directed.
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公开(公告)号：US20180231653A1
公开(公告)日：2018-08-16
申请号：US15682407
申请日：2017-08-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Vivek PRADEEP , Pablo Luis SALA , John Guido Atkins WEISS , Moshe Randall LUTZ
Abstract: An entity-tracking computing system receives sensor information from a plurality of different sensors. The positions of entities detected by the various sensors are resolved to an environment-relative coordinate system so that entities identified by one sensor can be tracked across the fields of detection of other sensors.
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公开(公告)号：US20190294871A1
公开(公告)日：2019-09-26
申请号：US15934315
申请日：2018-03-23
Applicant: Microsoft Technology Licensing, LLC
Inventor： Hamidreza VAEZI JOZE , Ilya ZHARKOV , Vivek PRADEEP , Mehran KHODABANDEH
Abstract: Methods, apparatuses, and computer-readable mediums for generating human action data sets are disclosed by the present disclosure. In an aspect, an apparatus may receive a set of reference images, where each of the images within the set of reference images includes a person, and a background image. The apparatus may identify body parts of the person from the set of reference image and generate a transformed skeleton image by mapping each of the body parts of the person to corresponding skeleton parts of a target skeleton. The apparatus may generate a mask of the transformed skeleton image. The apparatus may generate, using machine learning, a frame of the person formed according to the target skeleton within the background image.
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公开(公告)号：US20190220698A1
公开(公告)日：2019-07-18
申请号：US15870783
申请日：2018-01-12
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor： Vivek PRADEEP
CPC classification number: G06K9/6256 , G06K9/00892 , G06K9/6293 , G06N20/00 , G06T7/254 , G06T7/75 , G10L15/063 , G10L2015/0636
Abstract: Methods and systems for automatically generating training data for use in machine learning are disclosed. The methods can involve the use of environmental data derived from first and second environmental sensors for a single event. The environmental data types derived from each environmental sensor are different. The event is detected based on first environmental data derived from the first environmental sensor, and a portion of second environmental data derived from the second environmental sensor is selected to generate training data for the detected event. The resulting training data can be employed to train machine learning models.
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