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公开(公告)号：US11903730B1
公开(公告)日：2024-02-20
申请号：US16582840
申请日：2019-09-25
Applicant: Amazon Technologies, Inc.
Inventor： Apoorv Chaudhri , Siddhartha Chandra , Prakash Ramu , Amit Kumar Agrawal , Sigal Raab , Anantharanga Prithviraj , Ram Sever , Ita Lifshitz , Ayush Sharma , Anna Shtengel , Gal Levi , Rajesh Gautam
IPC: A61B5/00 , G06T7/11 , G06T7/194 , G06T3/40 , G06T7/00 , G06N3/04 , G06N3/08 , G16H30/40 , G06T7/60
CPC classification number: A61B5/4872 , A61B5/0077 , A61B5/7264 , A61B5/7278 , A61B5/742 , G06N3/04 , G06N3/08 , G06T3/40 , G06T7/0014 , G06T7/11 , G06T7/194 , G06T7/60 , G16H30/40 , A61B2560/0431 , A61B2576/00 , G06T2207/20084 , G06T2207/30196
Abstract: Described are systems and methods that use one or more two-dimensional (“2D”) body images of a body to determine body fat measurements of that body. For example, a standard 2D camera of a portable device, such as a cell phone, tablet, laptop, etc., may be used to generate one or more 2D body images of a user. Those 2D body images, or image, may be processed using the disclosed implementations to determine a body fat measurement of the body represented in the image.
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公开(公告)号：US11854146B1
公开(公告)日：2023-12-26
申请号：US17358679
申请日：2021-06-25
Applicant: Amazon Technologies, Inc.
Inventor： Brandon Michael Smith , JinJin Li , Amit Kumar Agrawal , Visesh Uday Kumar Chari , Durga Venkata Kiran Yakkala , Prakash Ramu
CPC classification number: G06T17/10 , G06T15/04 , G06T15/205 , G06T19/20 , G06T2219/2004
Abstract: Described are systems and methods directed to generation of a dimensionally accurate three-dimensional (“3D”) model of a body, such as a human body, based on two-dimensional (“2D”) images of at least a portion of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of at least a portion of their body from different views with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model or avatar of the body of the user.
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Patent Agency Ranking
公开(公告)号：US11631260B1
公开(公告)日：2023-04-18
申请号：US17132738
申请日：2020-12-23
Applicant: Amazon Technologies, Inc.
Inventor： Shashank Tripathi , Visesh Chari , Ambrish Tyagi , Amit Kumar Agrawal , James Rehg , Siddhartha Chandra
Abstract: Techniques are generally described for object detection in image data. First image data comprising a three-dimensional model representing an object may be received. First background image data comprising a first plurality of pixel values may be received. A first feature vector representing the three-dimensional model may be generated. A second feature vector representing the first plurality of pixel values of the first background image data may be generated. A first machine learning model may generate a transformed representation of the three-dimensional model using the first feature vector. First foreground image data comprising a two-dimensional representation of the transformed representation of the three-dimensional model may be generated. A frame of composite image data may be generated by combining the first foreground image data with the first background image data.
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公开(公告)号：US11450008B1
公开(公告)日：2022-09-20
申请号：US16803363
申请日：2020-02-27
Applicant: Amazon Technologies, Inc.
Inventor： Ambrish Tyagi , Siddhartha Chandra , Amit Kumar Agrawal , Viveka Kulharia
Abstract: Devices and techniques are generally described for weakly-supervised object segmentation in image data. In various examples, a first frame of image data may be received. The first frame may include a first bounding box surrounding a first set of pixels, wherein first subset of pixels of the first set of pixels represent a first object of a first class and wherein second subset of pixels of the first set of pixels represent background image data. Cross-entropy loss may be determined for the first set of pixels. In some examples, a spatial attention map may be determined for the first set of pixels. In further examples, parameters of a convolutional neural network may be determined by modulating the cross-entropy loss for the first set of pixels using the spatial attention map. The convolutional neural network may be used to generate a segmentation map.
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公开(公告)号：US10582149B1
公开(公告)日：2020-03-03
申请号：US15435896
申请日：2017-02-17
Applicant: Amazon Technologies, Inc.
Inventor： Rohith Mysore Vijaya Kumar , Ambrish Tyagi , Yadunandana Nagaraja Rao , Suresh Bholabhai Lakhani , Amit Kumar Agrawal
Abstract: A system and method for generating preview data from video data and using the preview data to select portions of the video data or determine an order with which to upload the video data. The system may sample video data to generate sampled video data and may identify portions of the sampled video data having complexity metrics exceeding a threshold. The system may upload a first portion of the video data corresponding to the identified portions while omitting a second portion of the video data. The system may determine an order with which to upload portions of the video data based on a complexity of the video data. Therefore, portions of the video data that may require additional processing after being uploaded may be prioritized and uploaded first. As a result, a latency between the video data being uploaded and a video summarization being received is reduced.
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公开(公告)号：US10325372B2
公开(公告)日：2019-06-18
申请号：US15385249
申请日：2016-12-20
Applicant: Amazon Technologies, Inc.
Inventor： Amit Kumar Agrawal , Alexander Adrian Hugh Davidson , Prakash Ramu
IPC: G06T7/194 , G06T7/11 , G06T5/50 , G06T7/90 , G06K9/46 , G06K9/62 , H04N13/106 , H04N13/15 , H04N13/207 , H04N13/356
Abstract: Techniques for providing an accurate auto-crop feature for images captured by an image capture device may be described herein. For example, one or more image masks for a color image captured by an image capture device may be received by a computer system. Metadata about the color image that identifies portions of the image as foreground and the color image itself may also be received by the computer system. Further, a representation of a user and a floor region associated with a user may be extracted from the color image using the one or more image masks and the metadata. A first area of the color image may be cropped with respect to the extracted representation of the user and the floor region associated with the user to generate a second area of the color image. In embodiments, a third area of the color image may be obscured based on the received metadata.
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公开(公告)号：US10027883B1
公开(公告)日：2018-07-17
申请号：US14307491
申请日：2014-06-18
Applicant: Amazon Technologies, Inc.
Inventor： Cheng-Hao Kuo , Jim Oommen Thomas , Tianyang Ma , Stephen Vincent Mangiat , Sisil Sanjeev Mehta , Ambrish Tyagi , Amit Kumar Agrawal , Kah Kuen Fu , Sharadh Ramaswamy
Abstract: Various embodiments enable a primary user to be identified and tracked using stereo association and multiple tracking algorithms. For example, a face detection algorithm can be run on each image captured by a respective camera independently. Stereo association can be performed to match faces between cameras. If the faces are matched and a primary user is determined, a face pair is created and used as the first data point in memory for initializing object tracking. Further, features of a user's face can be extracted and the change in position of these features between images can determine what tracking method will be used for that particular frame.
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