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公开(公告)号：US10713614B1
公开(公告)日：2020-07-14
申请号：US14225196
申请日：2014-03-25
Applicant: Amazon Technologies, Inc.
Inventor： Ohil Krishnamurthy Manyam , Minmin Chen , Liefeng Bo , Xiaofeng Ren , Dilip Kumar
Abstract: This disclosure describes a system for processing an image of an item and correctly identifying the item from a group of candidate items. In one implementation, as item image information for a new item is added to an item images data store, a determination is made as to the weight of the item represented by the image, and the item may be associated with a weight class. Each weight class represents items within a defined weight range. Item image information for items in the same weight class may then be used when new items are added to inventory and/or when identifying an item represented in an image.
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公开(公告)号：US10332066B1
公开(公告)日：2019-06-25
申请号：US14673739
申请日：2015-03-30
Applicant: AMAZON TECHNOLOGIES, INC.
Inventor： Ramanathan Palaniappan , Navid Shiee , Xiaofeng Ren , Michel Leonard Goldstein , Dilip Kumar , Gopi Prashanth Gopal , Ohil Krishnamurthy Manyam
Abstract: An inventory location such as a shelf may be used to stow different types of items, with each type of item in a different partitioned area or section of the shelf. Weight data from weight sensors coupled to the shelf is used to determine a change in weight of the shelf and a change in the center-of-mass (“COM”) of the items on the shelf. Based on the weight data and item data indicative of what items are stowed in particular partitioned areas, activity such as a pick or place of an item and the partitioned area in which the activity occurred may be determined. Data from other sensors, such as a camera, may be used to confirm the occurrence of the activity, disambiguate the determination of the particular partitioned area, and so forth.
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公开(公告)号：US10242393B1
公开(公告)日：2019-03-26
申请号：US14313904
申请日：2014-06-24
Applicant: Amazon Technologies, Inc.
Inventor： Dilip Kumar , Gianna Lise Puerini , Jason Michael Famularo , Amber Autrey Taylor , Thomas Meilandt Mathiesen , Jared Joseph Frank
Abstract: Described is a system and method for presenting event information to a user and, if necessary, obtaining confirmation of different aspects (user, item, action) of the event. In some implementations, an event includes a user, an action, and an item. For example, an event may include a user picking an item from an inventory location, a user placing an item into a tote associated with the user, etc. if the aspects of the event cannot be determined with a high enough degree of confidence, a user interface may be generated and sent to the user requesting confirmation of one or more of the aspects of the event.
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公开(公告)号：US10223591B1
公开(公告)日：2019-03-05
申请号：US15474946
申请日：2017-03-30
Applicant: Amazon Technologies, Inc.
Inventor： Roman Goldenberg , Gerard Guy Medioni , Ofer Meidan , Ehud Benyamin Rivlin , Dilip Kumar
Abstract: Multiple video files that are captured by calibrated imaging devices may be annotated based on a single annotation of an image frame of one of the video files. An operator may enter an annotation to an image frame via a user interface, and the annotation may be replicated from the image frame to other image frames that were captured at the same time and are included in other video files. Annotations may be updated by the operator and/or tracked in subsequent image frames. Predicted locations of the annotations in subsequent image frames within each of the video files may be determined, e.g., by a tracker, and a confidence level associated with any of the annotations may be calculated. Where the confidence level falls below a predetermined threshold, the operator may be prompted to delete or update the annotation, or the annotation may be deleted.
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公开(公告)号：US12229716B1
公开(公告)日：2025-02-18
申请号：US17728521
申请日：2022-04-25
Applicant: Amazon Technologies, Inc.
Inventor： Jason Michael Famularo , Amber Autrey Taylor , Dilip Kumar , Gianna Lise Puerini , Thomas Meilandt Mathiesen
IPC: G06Q10/00 , G06Q10/087 , G06V40/12 , G06V40/18
Abstract: Described is a system and method for presenting event information to a user and, if necessary, obtaining confirmation of different aspects (user, item, action) of the event. In some implementations, an event includes a user, an action, and an item. For example, an event may include a user picking an item from an inventory location, a user placing an item into a tote associated with the user, etc. If the aspects of the event cannot be determined with a high enough degree of confidence, a user interface may be generated and sent to the user requesting confirmation of one or more of the aspects of the event.
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Patent Agency Ranking
公开(公告)号：US12073571B1
公开(公告)日：2024-08-27
申请号：US17727452
申请日：2022-04-22
Applicant: Amazon Technologies, Inc.
Inventor： Boris Cherevatsky , Roman Goldenberg , Gerard Guy Medioni , Ofer Meidan , Ehud Benyamin Rivlin , Dilip Kumar
IPC: G06T7/292 , G06F18/2113 , G06F18/2415 , G06T7/55 , G06T11/60 , H04N7/18 , H04N23/90
CPC classification number: G06T7/292 , G06F18/2113 , G06F18/2415 , G06T7/55 , G06T11/60 , H04N7/181 , H04N7/188 , H04N23/90 , G06T2207/10024 , G06T2207/10028 , G06T2207/20081 , G06T2210/12
Abstract: The motion of objects within a scene may be detected and tracked using digital (e.g., visual and depth) cameras aligned with fields of view that overlap at least in part. Objects may be identified within visual images captured from the scene using a tracking algorithm and correlated to point clouds or other depth models generated based on depth images captured from the scene. Once visual aspects (e.g., colors or other features) of objects are correlated to the point clouds, shapes and/or positions of the objects may be determined and used to further train the tracking algorithms to recognize the objects in subsequently captured frames. Moreover, a Kalman filter or other motion modeling technique may be used to enhance the prediction of a location of an object within subsequently captured frames.
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公开(公告)号：US11688198B1
公开(公告)日：2023-06-27
申请号：US17457551
申请日：2021-12-03
Applicant: AMAZON TECHNOLOGIES, INC.
Inventor： Rajeev Ranjan , Gerard Guy Medioni , Manoj Aggarwal , Dilip Kumar
IPC: G06V40/13 , G06V10/94 , G06F18/213 , G06F18/214
CPC classification number: G06V40/1318 , G06F18/213 , G06F18/2148 , G06V10/95
Abstract: A biometric identification system uses inputs acquired using different modalities. A model having an intersection branch and an XOR branch is trained to determine an embedding using features present in all modalities (an intersection of modalities), and features that are distinctive to each modality (an XOR of that modality relative to the other modality(s)). During training, a first loss function is used to determine a first loss value with respect to the branches. Probability distributions are determined for the output from the branches, corresponding to the intersection and XORs of each modality. A second loss function uses these probability distributions to determine a second loss value. A total loss function for training the model may be a sum of the first loss and the second loss. Once trained, the model may process query inputs to determine embedding data for comparison with embedding data of a previously enrolled user.
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公开(公告)号：US11482045B1
公开(公告)日：2022-10-25
申请号：US16799502
申请日：2020-02-24
Applicant: Amazon Technologies, Inc.
Inventor： Jaechul Kim , Nishitkumar Ashokkumar Desai , Jayakrishnan Kumar Eledath , Kartik Muktinutalapati , Shaonan Zhang , Hoi Cheung Pang , Dilip Kumar , Kushagra Srivastava , Gerard Guy Medioni , Daniel Bibireata
IPC: G06K9/00 , G06V40/20 , G06K9/62 , G06F17/16 , G06Q30/02 , G06N3/08 , G06N20/00 , G06V20/10 , G06V20/52
Abstract: Where an event is determined to have occurred at a location within a vicinity of a plurality of actors, imaging data captured using cameras having the location is processed using one or more machine learning systems or techniques operating on the cameras to determine which of the actors is most likely associated with the event. For each relevant pixel of each image captured by a camera, the camera returns a set of vectors extending to pixels of body parts of actors who are most likely to have been involved with an event occurring at the relevant pixel, along with a measure of confidence in the respective vectors. A server receives the vectors from the cameras, determines which of the images depicted the event in a favorable view, based at least in part on the quality of such images, and selects one of the actors as associated with the event accordingly.
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公开(公告)号：US11328513B1
公开(公告)日：2022-05-10
申请号：US15806098
申请日：2017-11-07
Applicant: Amazon Technologies, Inc.
Inventor： Eli Osherovich , Ehud Benyamin Rivlin , Yacov Hel-Or , Dmitri Veikherman , Dilip Kumar , Gerard Guy Medioni , George Leifman
Abstract: Described is a multiple-camera system and process for detecting, tracking, and re-verifying agents within a materials handling facility. In one implementation, a plurality of feature vectors may be generated for an agent and maintained as an agent model representative of the agent. When the object being tracked as the agent is to be re-verified, feature vectors representative of the object are generated and stored as a probe agent model. Feature vectors of the probe agent model are compared with corresponding feature vectors of candidate agent models for agents located in the materials handling facility. Based on the similarity scores, the agent may be re-verified, it may be determined that identifiers used for objects tracked as representative of the agents have been flipped, and/or to determine that tracking of the object representing the agent has been dropped.
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公开(公告)号：US11288539B1
公开(公告)日：2022-03-29
申请号：US16876762
申请日：2020-05-18
Applicant: Amazon Technologies, Inc.
Inventor： Ohil Krishnamurthy Manyam , Minmin Chen , Liefeng Bo , Xiaofeng Ren , Dilip Kumar
IPC: G06K9/62
Abstract: This disclosure describes a system for utilizing multiple image processing techniques to identify an item represented in an image. In some implementations, one or more image processing algorithms may be utilized to process a received image to generate item image information and compare the item image information with stored item image information to identify the item. When a similarity score identifying the similarity between the item image information and at least one of the stored item image information is returned, a determination may be made as to whether the similarity score is high enough to confidently identify the item. If it is determined that the similarity score is high enough to confidently identify the item, the other algorithms may be terminated and the determined identity of the item returned.
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