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公开(公告)号：US09828097B1
公开(公告)日：2017-11-28
申请号：US15179773
申请日：2016-06-10
Applicant: Amazon Technologies, Inc.
Inventor： Pragyana K. Mishra , Dushyant Goyal
IPC: G05D1/00 , G05D1/08 , G05D3/00 , G06F7/00 , G06F17/00 , B64D1/12 , H04B7/185 , B64C39/02 , G05D1/10 , B64D47/08 , G08G5/00 , G06Q10/08
CPC classification number: B64D1/12 , B64C39/024 , B64C2201/128 , B64C2201/141 , B64D47/08 , G05D1/101 , G06Q10/0832 , G08G5/0069 , H04B7/18506
Abstract: Directed fragmentation of an unmanned aerial vehicle (UAV) is described. In one embodiment, the UAV includes various components, such one or more motors, batteries, sensors, a housing, casing or shell, and a payload for delivery. Additionally, the UAV includes a flight controller and a fragmentation controller. The flight controller determines a flight path and controls a flight operation of the UAV. During the flight operation, the fragmentation controller develops a fragmentation sequence for one or more of the components based on the flight path, the flight conditions, and terrain topology information, among other factors. The fragmentation controller can also detect a disruption in the flight operation of the UAV and, in response, direct fragmentation of one or more of the components apart from the UAV. In that way, a controlled, directed fragmentation of the UAV can be accomplished upon any disruption to the flight operation of the UAV.
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公开(公告)号：US09723199B1
公开(公告)日：2017-08-01
申请号：US15372024
申请日：2016-12-07
Applicant: Amazon Technologies, Inc.
Inventor： Dushyant Goyal , Pragyana K. Mishra
CPC classification number: H04N5/23212 , G02B7/36 , G06K9/3233 , H04N5/23206 , H04N5/23216 , H04N5/23229 , H04N5/23293 , H04N5/2356 , H04N7/183 , H04N21/4728
Abstract: An imaging device may be configured to monitor a field of view for various objects or events occurring therein. The imaging device may capture a plurality of images at various focal lengths, identify a region of interest including one or more semantic objects therein, and determine measures of the levels of blur or sharpness within the regions of interest of the images. Based on their respective focal lengths and measures of their respective levels of blur or sharpness, a focal length for capturing subsequent images with sufficient clarity may be predicted. The imaging device may be adjusted to capture images at the predicted focal length, and such images may be captured. Feedback for further adjustments to the imaging device may be identified by determining measures of the levels of blur or sharpness within the subsequently captured images.
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公开(公告)号：US20160373722A1
公开(公告)日：2016-12-22
申请号：US14744480
申请日：2015-06-19
Applicant: Amazon Technologies, Inc.
Inventor： Pragyana K. Mishra , Dushyant Goyal
CPC classification number: H04N13/178 , G06T1/0028 , G06T2201/0051 , G06T2207/10012 , G06T2207/10024 , H04N1/32229 , H04N1/32309 , H04N5/232 , H04N9/045 , H04N13/15 , H04N13/207 , H04N13/271
Abstract: Depth information may be encoded into pixels of visual imaging data according to steganographic techniques. The depth information may be captured simultaneously with the visual imaging data, and one or more representative pixels may be identified within a region or sector of the visual imaging data according to a pixel traversal strategy. The depth information corresponding to the region or sector may be encoded into one or more least significant bits of the representative pixels, and a modified set of imaging data including the visual imaging data with the depth information encoded into the representative pixels may be stored in a data store and used for any relevant purpose.
Abstract translation: 根据隐写技术，深度信息可以被编码成视觉成像数据的像素。 可以与视觉成像数据同时捕获深度信息，并且可以根据像素遍历策略在视觉成像数据的区域或扇区内识别一个或多个代表性像素。 对应于区域或扇区的深度信息可以被编码为代表性像素的一个或多个最低有效位，并且包括具有编码到代表像素中的深度信息的视觉成像数据的修改的一组成像数据可以被存储在 数据存储和用于任何相关目的。
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公开(公告)号：US10939187B1
公开(公告)日：2021-03-02
申请号：US15234719
申请日：2016-08-11
Applicant: Amazon Technologies, Inc.
Inventor： Dushyant Goyal , Pragyana K. Mishra
IPC: H04N21/8541 , H04N21/472 , H04N21/81 , H04N21/435 , H04N21/845 , H04N21/235 , H04N21/25 , H04N21/84
Abstract: Disclosed are various examples that relate to providing an alternative viewing experience for video content. A semantic graph corresponding to the content is generated. The semantic graph is traversed and the video content segments corresponding to a selected attribute within the semantic graph are played back in an ordering that can vary from a linear representation of the content.
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公开(公告)号：US10282902B1
公开(公告)日：2019-05-07
申请号：US15192577
申请日：2016-06-24
Applicant: Amazon Technologies, Inc.
Inventor： Pragyana K. Mishra , Dushyant Goyal
IPC: G06K9/00 , G06T19/00 , G06T17/10 , H04N13/211 , H04N13/00
Abstract: 3D models of objects in motion may be generated using depth imaging data and visual imaging data captured at different times. A 3D model of an object in motion at a first position may be generated at a first time and projected forward to a second position corresponding to a second time. Imaging data captured from the object at the second position at the second time may be compared to the projected-forward 3D model of the object at the second position. Differences between the imaging data and the projected-forward 3D model may be used to modify the 3D model, as necessary, until an accurate and precise 3D representation of the object has been derived.
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Patent Agency Ranking
公开(公告)号：US10205871B1
公开(公告)日：2019-02-12
申请号：US15645434
申请日：2017-07-10
Applicant: Amazon Technologies, Inc.
Inventor： Dushyant Goyal , Pragyana K. Mishra
Abstract: An imaging device may be configured to monitor a field of view for various objects or events occurring therein. The imaging device may capture a plurality of images at various focal lengths, identify a region of interest including one or more semantic objects therein, and determine measures of the levels of blur or sharpness within the regions of interest of the images. Based on their respective focal lengths and measures of their respective levels of blur or sharpness, a focal length for capturing subsequent images with sufficient clarity may be predicted. The imaging device may be adjusted to capture images at the predicted focal length, and such images may be captured. Feedback for further adjustments to the imaging device may be identified by determining measures of the levels of blur or sharpness within the subsequently captured images.
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公开(公告)号：US10158840B2
公开(公告)日：2018-12-18
申请号：US14744480
申请日：2015-06-19
Applicant: Amazon Technologies, Inc.
Inventor： Pragyana K. Mishra , Dushyant Goyal
IPC: H04N5/00 , H04N13/178 , H04N13/15 , G06T1/00 , H04N1/32 , H04N5/232 , H04N9/04 , H04N13/207 , H04N13/271
Abstract: Depth information may be encoded into pixels of visual imaging data according to steganographic techniques. The depth information may be captured simultaneously with the visual imaging data, and one or more representative pixels may be identified within a region or sector of the visual imaging data according to a pixel traversal strategy. The depth information corresponding to the region or sector may be encoded into one or more least significant bits of the representative pixels, and a modified set of imaging data including the visual imaging data with the depth information encoded into the representative pixels may be stored in a data store and used for any relevant purpose.
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公开(公告)号：US10061956B1
公开(公告)日：2018-08-28
申请号：US15387275
申请日：2016-12-21
Applicant: Amazon Technologies, Inc.
Inventor： Pragyana K. Mishra , Dushyant Goyal
CPC classification number: G06K19/06 , G01S17/74 , H04B10/1121 , H04B10/807
Abstract: A reflected light identification (RLID) system uses light to communicate stored information across long distances with minimal interference. The RLID system may include a light source that directs an incident light signal to an RLID structure, which then transmits an encoded light signal to a sensor. The RLID system may include a passive RLID structure (i.e., a structure that does not include power source) such as an RLID reflection surface that includes layered reflective films that reflect the incident light signal back in multiple reflections that serially encodes data. The RLID system may also include an active RLID structure (i.e., a structure that includes power source) that uses energy harvesting to extract and accumulate power from an incident light signal, and then uses the harvested energy to transmit a return signal.
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公开(公告)号：US09667879B1
公开(公告)日：2017-05-30
申请号：US15368324
申请日：2016-12-02
Applicant: Amazon Technologies, Inc.
Inventor： Dushyant Goyal , Pragyana K. Mishra
CPC classification number: H04N5/2353 , G06K2009/4666 , H04N5/23212 , H04N5/3535 , H04N9/045
Abstract: Blur metrics may be calculated for each of the image pixels of a digital image of a scene captured using an imaging device. The blur metrics may be indicative of the level of blur expressed in the digital image, and a blur image representative of the blur metrics may be generated. Subsequently, when another digital image is to be captured using the imaging device, pixel sensors corresponding to high blur metrics may be digitized at a high level of priority, or at a high rate, compared to pixel sensors corresponding to low blur metrics, which may be digitized at a low level of priority, or at a low rate. The blur images may be updated based on changes in blur observed in subsequent images, and different pixel sensors may be digitized at higher or lower levels of priority, or at higher or lower rates, based on the changes in blur.
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公开(公告)号：US11068970B1
公开(公告)日：2021-07-20
申请号：US16363414
申请日：2019-03-25
Applicant: Amazon Technologies, Inc.
Inventor： Dushyant Goyal , Pragyana K. Mishra
IPC: G06Q30/06 , G06Q10/08 , G06F3/0484 , G06F3/0482
Abstract: Items, such as produce items, may be placed in containers, imaged, weighed, and stored for subsequent retrieval. Images that depict the items and attributes associated with the items may be presented to customers via an interface. Upon receiving an indication that a customer has purchased one or more items via the interface, a container that includes the one or more items is retrieved. The one or more items are removed from the container and packaged for delivery to the customer. The resulting empty container is refilled with new items, which are then imaged, weighed, and stored.
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